{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ac9b11e2-9363-4d67-8306-5d87cdd83e44",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# <center>Python程序设计基础<center>\n",
    "## <center>第四章 Python 数据结构<center>\n",
    " <center>沈万福<center>\n",
    " <center> 办公地点：第十教学楼414室<center>\n",
    " <center>tel:18822265292<center>\n",
    " <center>mail:wfshen@tju.edu.cn<center>"
   ]
  },
  {
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CYgj/J7wf/SbobtSfbY5jSIaIYGyG8BDRQ12IZMEQTJ3Q4bgO5A7gAUKPQh8jL+VWgvvk/jB+UzZkBf2Pc/F8QaRCXalPIC4sycOSOqB/MbsdkTwYwZmUiqEDXJtzHa/FgCY7vHzGl8DiETZCwQg74wNjHwo/CRdnICQQID5yWD9u1JD4CFH+icVEsMhLIgSNcTeEmjF+BzArGUQCooPwkMgL+IDBBRdcYKQKwkOYHfvDMUB+xuTA9rkmdYRkYTFAwBBOykVQ+LixKpCfgYAIGRMnsN4TyE+eSmFiOxC2+P4A1kncJ0KFcOLp4VkhxCw5xvMKjY/D4XA4HI6BDXQKFHkiZNBLjj76aNNtmAkX3YnjLPG2BF0CoHsxeQDjTTBK48Hg/MMPP9wIDWN+iGA59dRTLT+gLHQMEusA3QXdA2MtuhH6TNybBNCl8DZRR8gDM7sxFCAcp06ExGG8RadBV4SUQN4oG90OogURg9hBatAZOYfrURYTWsXHYYf7BKxzv+EYuhx6XdCXgr4Iwn2xTdQQBA0SRl2IEGJcOYZqnjPhfkTb8NwcPWNAkZ3wAZH48Ij7PP300y0GFMCImZmDJWycD5dYUVKIJ0UQGcjPWB7Oxf0a0lvf+lbLE8A6VgyEB6tDcF0iYFg1TjnlFPuw8caEDxewTpwnY39+/vOf20AziA+eFY6RqD8CThzqoYceaoKG0BGyhqcHUoHrkiXsnuvg2gyD4Wh0sHogSFgACFljikMsLQgcAgQR5H5JCD3eGGYS4dpcg2uzBOEcCOSXv/xlEy5C4LBQ4AUiRhVXL/t4lhAfh8PhcDgcAx/oLege6CmEnUFaUNDRtdCV0GEIc8f7gp6CnoGRlogQQue/+MUvWkQK+hKeFLw8jPnBoEp4PeOmgx6CnkF+jMYYXtkfdCz0ELwu6ERMKgDCcYzSTKAEcWJYAgZpdDDKDOSJ8TpE+HBdvDqchx4EicJgDpHhHrlX9jOrLtNdA85HJ4IocX+M4WGmXYZC3HfffWbc5neIqCP6Yghlw+hOfggbM9qiQ1E+9QLk5T6ZTY5IJAzZEEeuw5JxSBwjH/fqeC0GDNnhQwlgnReOEg+5YapCBsxDevgQYeYQGT4qXJZhNjbOQUAgL5ADfoAKghDWmXwgCBQgPxYJhJUZ3CiHfcROko8PF7IBkYifh2uVuvGRss54IhoCWDnnk5eEoEE4+IARzCDAeKnw9IQyISlcA5aPsAXvTCB9lI/7loSgsJ+yEDIECAEkD2UgyNSBxohJEHhePBvOoVzC5BiAhxeJPMTBsp9zsHYccsghwnTdWGMcDofD4XAMfKAjAHSO733ve6afoOyj26Af4MVAN2LsDeN40H0wimI45ac+MBwzhprxvgwBYGwKIfMYhtHdwvAB9A08RhiTCcMPXhHORxeDTECeiIqB7FAPzsG4i65EPnQr9B5IB54nDOCQLMr6yU9+YkQK3Yv86IB4mDD0ErIPWfr+979v45UZOsB9cH+kgPAsCGtjDBLED4LCtcKYa84nHC0Y2qkvQEfDA4UXhzLRFdH38OagC4Yfo+dZcg51RifD+8N9hGs7VsWA/FFRPhAYMWNnIDmwZlyLMHViLQk9Q0hg9Xg6iMFEkGD0KPGQAj4irBKQGT4q1kl4VhA0hAePDB8WM3vgEYFY4RViEByWAcgEZAoiwdgbhI64VASZD5yymdiAfTQQEARiL/ESQRwQCELkGIiGFwfCxTXJjzDgsYGYIdzcE4JLvCouWASVZ4DQUyfC2oIXi7oRlofwYqGAZHFN6sAAN+6f+vEsiAdFIGmMcNdieeE58dywujB9N/kReKwe1ANBxEVMY+VwOBwOh2NgA10IHQK9BoWdGVoZaxxIAMdR1BlLjN5zxhlnWHQNulQwNuOpIKoGIoNhFb2CY5SDkZo86EDsR8fBwIwuRGgX+/D0YJxGJyG8C92HMjESY6zGKB1+BBSdjDA1JhVAx2FGM/RCrocug87FPkgG5WP8pTzqwaxnJOoVDMzcE+Fx6F0YjtHNIHLofRA+6o2OxnGicIiGgfQxhhy9D10tjEVCb0UHI1QNjxB1IR/3Qt0gSjfddJORRcpC1+Jc6kNdwjN3ROBHRRP6AQ4YGoig8ZJZ8oExcxqkgQ+ajx1yAzMPP3DFR82Hx0dDHmZYYyAchIaPuhIo8Qgx4WYIFh8kJAHLA4QD8oCLFoFCeEKIGAJA/CmAROGehQBRV8ohPI5zIEd4SyATuFv5sBEk6hi8Kz19xGE/CcKE0GBRwZICQYKgYCHhWpSF0COo3AvXwhVLA4AVBEsF9w8JgtBA8IhDxUKBa5nnRCPCs6RueJyIW+W3hjgWr19PdXU4HA6HwzFwENRIlugdJHQf9LA4MCqjR6GHhBD5nhDGO6MDAfQ3ykbnwAiMjoe+QXl4Owjb51qQH6JWCO9nX1wHCVEsgONE1gB0MnQjjOHx/FyD8iEPHA/HWFKXcM9hPx6bMMEAdacuIZyffdw31+ReKI9yuUZ4HjwzSBGeJ+oKwSEfhIgIG8rmHrkedaYc9pMnXIMU8jhWQp9Hol+SHSqkr02UtmjSrRICs6rQrA6cF2CkJ6Hnxd67fQy6L+RTimD5AB8Jx1/vQ7HHVT7MuZQTHiHb4RjF2zU4xG4tM+S3f+VyrD7l64a8LBPJqCCrX6l8HzFQjl2vAqE+8XtcpewyqE/IByrrFe4l/gwrr0e9QjkcC88tXLen+q0rSlqE3ZOVyXWichMcCOW/8cs4HA6HwzGwEXXzUtA+k24zyUZ3/xn1r+vboZruUEa3LlDeF7YDKvOaDhHLw3bYF46D+Dqo3K5EKKMnsB/9hmVPeTg3ft2QJ5QZv+7qzu9pfxyrKyN+3XgeEN8Xzgn3wX70ybXBqqVqWeXlQIQ+m/5JdsqTMCu9yekLUCJSUuZaSmmNy1VlMZDfjKMbEd0tKukp6FIbD/1L6bfA0pgQWDvZdjgcDodjs0VJ1amidpt5TSlV/UglGI/+U2VQlUJyRWN+HQMbpbg+rbB3H4zI+m8gqdn9lux01yiR14etG6rcQn2MBvGCSrjpoiyOAQ77FvgKsLJEwpfo9kZFqewEczgcDofDsRpEMSzaaxKxoQuCZkqqTBnRwa5sXatbDzcLlMnOSn2bXZiRUahM4+rWtTZ19FuyU5ZIexmR8R5lN69LfD68irQecoHcHMAb500HIwTAy1M0T0/RBDIjUVyvw+FwOByO1QGGE9ZgN5EXB29PUdkOnp4ErMcx8BEiYxTEzKBpGdExh0K0XylCtLKJo/+SHapErfRBd7+PEmovQojq60Rnc0FOSQ0imOomt/phaGNsVodugYwG6DkcDofD4egZefpP/UefSh+aZNyt6lvoWflkQreTrl1tVuB7KOg3oLo1xCaR0m8hqd+JDSCR6ijTJo9+THYiD46xTV6A1hCBjI6xj4VbHzYHlEQF0dawQBnFsW/C3K18EnwG0TT7DofD4XA4VoO8dpiEryXzql+lEkpwSpIu0qtqT6v9KinjqtVmgbyyWnSrJLoUSnZZ01JW0B3aphQhWtnE0X/JTjlcLXKtKbSGCaYPURRVOHOJLt3VD6vt2OBIFjLKZVIRubEd+jmk+D4UgfCs5ewjDofD4XBsrrCYCGZ31XUMyJgSW/Mlmd2ak/ktndKZS9vkBY6BD6Z5Suc7ZPLwOtliRL3U4N0xvTopRSU5rA2UqSr6L9kpV4mBc4inPfYCUyknJJcsyIrSMnl64WOWxzGw0Vg9TMY2jpMhiSEqeKloSm39BiKXDoAEuWvH4XA4HI7XA72m/ZSFeXhKMr8rKffPaZOHZjXLsjY9WsqoqsX4aMdAR0r1pqquZbLX5MFy5G7jZHD3UJGUFCyUzcPYeh/lGhGxhpfHogeLaYsjzCZyMq/rFbns+b9aHsfARn2qUSbUTJI9J+wrI6vGSEb/9MvVTyTy7ZmFyv53OBwOh8OxOtikPozToffMJ+Xql5vlvzOalePUyZQRdTK8KqHdazAkOgYyMByncu2y5chGmTK8VmpLgeTq16E6Fl8J3p+BgP5LdlYDqkrSasuKfHN5r2MgY15utvzv1btkUesi2WP0PvLmifvb7Gs2k4x+B4Q3JlLud3c4HA6H43VRKkheokkImnMF+frtS+XgybVy2JRqqU9hYE53/9C4wzFQsEmRncpqFjYZiuZ4I+hMdMj8/Ey54anLzdpw6NQTZVrDdpG9Addfoks/5BrL63A4HA6Ho2dYRERBu03lM7fNXCGPzsvL6TsOllE1BRsPTWhbKllVzu1wDAzAdTZZCo8x39PAT7X5OpmUniJbj91GlslieXLxI2VXvH7ASnaKeHgcDofD4XC8Lko20U9RGJ5z7+wVstv4ehldoyRHVUGzHYbfc3A4Bhg2YX8lQulpoCdmA8kUMzJt2G7SUDdc5nfM0r38NoAesDxuhXI4HA6HY02wfjORkmeX5GVma0G2G16l5EfVQCU6afrVKGbC4Rhw2GTIToLxGbFkflhPAz4V03mbHWacTJJjR58shVxB5rbPZkoZKfKDo8WBMjmiw+FwOBy9h0SxIDPbivKfF5ZLlXadozOEr2l3qiyIHxQt+symjgEK/cw3TWCh8DTwE3Px5RNFSZVKMjI9QkbWjpNFHQukYDPGQIjKv7njcDgcDofjdVCUGS15mdfcLlOaqrT/xK+T00Q/ijronh3HwMQmS3ai+cA9DfSEW105D553qU3Xy4TBk2V2x0xpL7UpGcLD578J4HA4HA7HmpDVPvPVpZ1SKiZl6qAMARKYEzUVyr2tkx3HwMQmNfV0HAVTgQcg4rcV2h3T9stLEN9fidW1VZXl9nTu62F156zuehsIyaL95rN+qCn9vyjzCzPlghd+KydMeIdsW7uzZDNFqU34uB2Hw+FwbMaw/ln/0z456qqVuqh6Z+uE/iseXZKTix6aL5n0IPnCAQ0yKFWUXJKfl2QcLL+rkgxZ1wmokQwvCOqkDTVYS7yeCrqmMuPHVldOOO/1rhNHT2Wtbp9j04C+KwZGbJrgx44GWkqqLPFCuhPbYV95SeO1yv6KlChqoxNLPeW1a5FXy7LyYsd62mcpdv1VjpfLr7yXDZXsnzbGktSGO5WSIalRIrmSzMpPl850h9SUMloLh8PhcDg2c5SIiOjUxO/psJ0VKealoH12l27OXJqQbD4hkwfnpCGtekAiLTVKdDKaO219OyetHwIZYFksFi2F9Y6ODuns7FxlH8vKc1gWCoXuY+F4V1eXnR/yxcsBIV9P4Fg4H4RzuA4IZYUywjJedtgX7iNsOzYdoK86+gGCQCFgwWIQF7K4cMX35fN5aW9v787LdjzlcrnuxiOAdfYFIachAEH443lB3KrR1tYmM2bMeE15vYey9URbYf7SqbRUpaplSfMS6cpr49Wbl3Y4HA6HYxMAXWGJ7rJkZslyz6nr2n9rDy78hs6i5jYp5XMybliDHS/3roqVa28U6AvoHtls1nQKdJDbb79d7r33XtsX9BKWgPWWlhZpbm62FNZbW1tNtyDddtttcvPNN3fn51z0l2XLllkKukwcYZv8XPuWW26xbcrlHJbhmsuXL5cVK1Z014nlokWLunWjUNaVV14pN910U7eO5th0kNCX6OpiPwCNAgJ3+eWXSyaTkbe+9a0yePDgbiF7+OGHbbn77ruvQj4efPBB+fWvfy177LGHHHfccfKXv/zF9gdQLkJ98skny7777iupVEr+9Kc/yVNPPSVnnnmm1NfXy9e+9jX54Ac/KBMmTLBGI51Oy/Dhw6WhoaFcihih+u9//yt//vOfraH40pe+JHvttZdUV1dLMonru5eEv/x15stjc1KllFz00u9kYcd8OXTy0bJD3W5WX4fD4XA4NleYH0L1gmRJFf8Ev5sTkRxC/lOqB+T12JfubJFByaKcsc8wGVOT1/60WrkRIWzQHXLr/+vRlcfVSHSO3/zmN0Yy0DdYPvroo6YrbL/99qYvgLFjx8o73vEOmT9/vjzwwAOm/6BHkB99A3Lzn//8x/L++Mc/tv1nn3226TgQounTp8shhxwi2223nWyxxRbyr3/9y65HXUh1dXV2fNiwYXLhhRcaefniF78ol112mZEZ9Bn2oWu9+uqr8vLLL8tHP/pR2WWXXWybvJ/73OdMtwr45Cc/abrRV77yle77cPR/6He16YaxDTQg5LW1tdYA3HPPPXLNNdfInDlzZO7cuTJz5kxrKJ599lmZPXu2JfYhbDvttJMcccQRto2L9cgjj1wlvfnNbzbrBAQlNEhXXXWVuWKxUNCY4K3B6kFjccUVV8j1119v1443YPfff79cdNFFRoi+8IUvyAUXXGAErNdITkB3FfDrRA3y8LqR0pXvksWdi7SB99nYHA6Hw7G5I4p+iAJ2IurCpAM28YB200VV91pzRRleXyOD+cWGUt5C0gEkh3M2FLbaaitLW2+9tWy55ZbS2NhoxlvW2ccxdAkwatQoOfbYY+Wd73ynnH766fLud79bjj76aCMrARAoCArloNdAUCjrtNNOk7333tu8M1dffbXpOjU1NWbgvfXWW41IAXQZzkdf4VyuM23aNKsD6295y1u6jcsk8kGcKvWbUA/HpofU/ynK644+Bh6K0aNHmwUDInPjjTea+xXX6QsvvGCWh0ceeUQeeughufPOO82iccMNN8jhhx8u2267rUycOFGmTJliAkwaP368NDU1yTPPPGMkigbmlVdesXPf9a53WWNBvueee848P1ybfZMmTbJzIVgIOwL+qU99yso466yzZLfddrN6XXvttTJy5EiZPHlyNzHqDfJDk11KRM0xvwWwJLtYXm5+Uepq6mVa07aSTvq4HYfD4XBsvgh2waSFrulKoqg9Z1L7ZsbUFqW9oDrF9A7ZcUS9bDesJKlkXo9moqg3XYt67pVh9OsKdIAQWva///3PwsLwwLBEd+EYBt2wD+MsRAdSQ2g8RlZ0lSeeeMJ0kueff15OPfVUqw/6BuejeyxZssQIB9EpeFkgOpTFNfHM7LPPPt16D14a9CkMyHhrFixYYPVD7yE/YXWHHXaYGXcxJu+8885WJ8q87rrrTAfieuhf1PGuu+4yQkWdX3rpJdPTuBZ17A3dx7Fh8A2Fe3b6ERAWBOfEE0+0kLT3vOc9RkLw2uy///7ykY98RM444wzbf84555jVAlcv1g6sJVVVVSaICDDLQJogK4TGIay4X9mPoN99990mvIsXL7bGgH1sI/gQL87FQnL++efLwQcfbKFr22yzjZWFdwdrzA9/+EP52c9+ZnUPVpENDm1D+FBJEJ9BmSFSk6mVZZ1LpKPYZlkcDofD4dicEdRtlnh2onXtl4slacuWpCpRklGN0CGMh5AizVnusiM/0PohjJmBhCxcuFBmzZplegYJYsMxjLOQhBAef8kllxj54BzIzNNPP20EAtKBrsJ5AUG3gDQRtv/Xv/7VQvgJaSMsDR0GTwy6CQSF61An1tGb0HW4FqQFzw/6CtEt5GMdHQl9J4TBAfQooleIeiFhWB4zZoydwzrjiNDNuI6j/8PJTj8BggVxYfwM1gm8L3hZpk6dag0GIWd///vf5R//+IcJOI0JAopgEt9KzOvnP/95efzxx420kBiTgyAizDQoeGwuvfRSK4/9CDv7KYP10DhRLiBsDSJzwgknmEUGywuxr4zbwepBXmJY8RLhMqbMkEKD8UZRTGhZ2KeKGUkUU1JIFmVs7USZ0DRJ5iyfITM7Xy7ndDgcDodj80SyBH1RapNUvYBBOKW0/Rg3cQ+FVFJmr8jKuEynTByUl5T2pYlEtY3rIVqC3jo6Z/36bYgCCYMresYnPvEJGTdunFx88cUWAo9hFD0F7wrRJ29/+9vlBz/4gUWjMG4GEkP4GmN4MOgSQQKhqQSemu9///vmfYEMEe7GuBqiUgLQPdBNIC54fAjN53qEu33ve98zzw/1xMMUQtfQvyBK7A9gPDNG5e9+97vyne98x5bnnXeejR9i++tf/7oNE/Axw5sGnOz0EyBkDKZjAB7hZgHB+oCQv+lNbzKBZcwObl4aF4hMAAPxmDTggAMOsLE8bIOQB6Em4Qki7G3XXXeVHXfcUYYOHWr5STvssINZQxgsiAsZT9CQIUOsscDbBPEJnqdTTjnFBu9hqaHuNC6VdXqj6G56WSnyryi16TpprG7CNy9LOhZHxx0Oh8Ph2IwR9Zf8H61ZT1wq8GsNsrwjK6ObaqUmk1Jig4Kesh8VjbJG+cNifYBuQd+PvkJ4O4nxMOgjzMbG5EqQB8Yho7/g6YFsEIUC8cBjw8QGGFhJGG8rgX5B5AkEiWgWQvyJSkH3wMgKqEMgX0EXYZ086DaQE+oK+SIMjjyQo5AHYASGKD355JPmFSLdcccd3dEw6GUYgENZjv4PJzv9BAhM8KpgZQhA4LAwHHXUUTawDrKBZQSCwTlxQeN8EhMOUA4CC8gTbwAQ6KVLl1oYHI0GcbBsk9gmRpUGKJSNyxYvD16dsMTqgqeJmd3wIoW88fpsCDC8UltmLdcWYj98VkpJk5Kd6nSNzGudqwf4h/8HjxJ1YI3zWOfIhq2Tw+FwOBz9C1E/V6KjtD6RRJ9YlGwxIc0dBRnZWCN1aVX7Ip0eP1CZEZVRJgfrA3SMkAgZg3yggxCWxuQDeGMYM8xYm5/+9KcWIg/wADEmmCgRPEKf/vSnzcODHlMJjLAQHIgUZInJmRjHjJ7EtdBvgPX7Pegi5GNMEDoOY3eIngHoXNQb3Yjz2IaAMW4IksPMbZAcIm7wSBEOF8B5jv4PJzv9BKGRQNBYIowIF0QCzwuTA3AsCDVkJ+QPJAaiQogZZIQGIUxTTQJYMgiDw43LPqZuJDSNiQYISwvjfRicR0MUwtGox4c+9CF573vfa+5l0vve9z75wAc+YMdxU3N9ygzLcM03CkpJMIKSlRRuetzvJZnQOEmGJIbLK60vdzfoRmq0Pvh/2BfAlsPhcDgcAxVwHPpJ6yOjWQcUUV+4rF1kxrKiTBxWKw3plCr10dFk0k7QrjXqW3VHdGA9gC6AzoChlSU6BDrH+9//fiMH/KwGUSIhnAz9A+MsUS0QHqaPJqyNyBb2QzYqgUEWjw76CLoG4XGMH8abxHXxxDDOBpISyBJ1QZ9C18GzRMQL45CZpIBIGHQeSBREB28NYJZaImkIV/vGN74h3/rWtywxbpm6ca9Bz9mQ+o6j9+Bkpx8BYUOAITTEmUJoGLjHDCG4SxHm4LUJQgk4B0J06KGHmtuYCQyYkpGEoAfgwmXmkeOPP94aFBoiJj5g2kUsJXh6DjroIDnppJNsWsYABJvrM7CPMkiss486xq+x4aHkCeOTtiXWljNbujbQTalBMig1WIppbVhp0GPWLIfD4XA4Nicw5UDUE+v/2mnSXxYhMNp5duSL0txZlNpMxHKCsr4hEZR+9BGIDD+fgeGUSBQIBhEq6A6Mz/nJT35i45HReUI9OC9scz7EqBLM/HrMMcdYXlL8HiBXGHmZ+ABiw6QFHMc4jKcJIoVuxLghxjbjPeI4egyG3qDjsETvgghxjaDfkDdsx6/r2DTgZKcfAUHCO4PbF08O1gjWmZEN4aIhgAhBdsIsIgDhpBFg/nlIEI1KWHJOaNhYpwH51a9+ZeFoDK5jUCDjdvgBLcrFSkJMLecEcC6/qxNPhK/hQWIabAb29RaiaoSGhWXJBlLWJ5pkcNUw+7HRguTLGUM+bQTLaxFW3XI4HA6HY6AhCtlmgqGo/zYCVErIiq6StGS136xa2RfG+/gNBcpkRjV0DMYZ44EJegx6yogRI8wIC2FB12A/+gWTDRDFgj5BJAm/+YcHpxKUgYG1EuhOjP9hzHOYNAkdCqALoed89atflQMPPFB+//vf2zgiwuCY+IlrEgrHTLiQHWaTI+QOwzD3Eyc8QZfqjWfn6F0k9KX5W+unYIDeueeeaxMKYA35+c9/bsLO7+owIQAWCjxAxLhiMQmAtDCAjsF+TOHIJAJMKICFg5hTLBpxoWUKR0LeEGr2YdWgPBoDlgwc/PCHP2znB2KD8EOe/vnPf5obmJjc3gDXYbaYYqqgy2gQIuQmXczIk0sflX8u+pt8bvuvSn1pkNUdEIdcSmjjpPmN6ET/HA6Hw+EYkEAdp3dM6/8lPDqq2RW05+vM5uTaFzvkjplZ+cmRw6WW0LWNAHQLdBHGxqDDQCTiiKuerOOJwcNCWBueIPSLgDB9NeUE4kGUC9uA0DI8OxAe9Bh0FY5j8EVn4lz2EQZH+UTCsA/jMREugwYNsnwBQZeII9QXgzT54zqXo39D32fCyU4/BkKFJ4YGAwHlVZG6lfoyWQnblQiNQjy/kQdtDED83Mp1EPJx/bDeE8j/esffCEpaX6KJC8m8TUzA7wXgy0kX0vJK+4ty+byL5D3TzpaxiQlSLOn9ajWiqTSZnAEPT7lePT8ih8PhcDg2eUS9vfbVukb4Gl1eUfvC5Z15+efTzfLMkpL86LBhktkIZCfoEHFU6ilB5+gp75oQzl3X88N54PXODXniqMzbUx5H/4S+KwZAOPorwrSIEB1Iink1lHiwDIIWCE0cCCUpfk5AfD0gNABBmDknlBH29QSOhby9B71P/ac1sT82kuVxO/V1DVInDbKis1XroIdK5cYnVMfbIofD4XBsBrCxrdoHam9e7gIj9a69WJJlbVmpSRYkvZH7xLhe0RMqj7FduS/oOvH9odzK/JXnxlFZTuUy4PXKWN05jv4PJzv9HMFjwhK3Lq7WuHs3vg4QwiDUIW88z+u5asM2+eOemsp8AewnX295dSLQcNOwRClhZEfroy17babWyE5bZ/mXljWLN0EOh8Ph2NxAL03/WDK1LkxWUJK2QklWZAtSp11/zz157yHoI6vTISrxenkrj4X1nvaB1eWt1Ffi+UDldhzhWO/qPI7egL+xjQSmfyRFzubXpnA8nsqmmlWS+eLCtuayFFuPZHFlPpYhdZ8fzgvnhH2h3Fh51COUGW2vPGapnLey7hsqcemiTUCgLXVBK2qX40hRMvr5TqodLQtb50tO/6hnUo8VqBNTbxajhsnhcDgcjoGMqHfW/lz7Pjw89JWFYkFmNpekOVuSsUOqNJfNXSoW38Eviupx+lMD3aamnK6+0ZTXzjieVpuHZUgV54T9Oa1U2Nd9Xjyt5nw7r7yf9bC9yrVDftZj++P1DKk7D9uUV96/bqlgiT+0mOgd6LIUrtqpydEb8DE7Gwn2YSsi9fu1Sri/hJ7BlNLFRM7G4dhYnASNsz6/YlKyqU55fOEjMqvlVTl86vHSmGiwZryQSElKiY458428GZtzOBwOh2NAItIxlOwUo0iOgnaT+UJern45J7e+sFgO3HqwnLp1RrtPxrRmTM9mMgPtTHUfYWGQJKiQo9dQDrXntwJB0d4FugqeB96drqRcX9nQSCj8qW4s6EceWVt6Thzz9NpUlKw+PF3nGWpLQINOw8yOlNTIyLrJ0trZKp2FDm2ssZDg3SFzBC1Cd3nz7XA4HI6Bj9DbsWTa6ea2LusDB9eiTkOE6FutC7V1+tO8qtpdLBNMbOCpt1IpyYy3moyQpvR5401Srcb0FN6Fq+S9BffsbGSsTvGOGh7Ha5DTBkDbBaaSjhrohIWpJYVJNbXxLiblZ098Vw6ferRs07CDNh+MSdKnaQ9Un7aeZ8YS/XM4HA6HYyAi0i00aYdHP5lT8rKkPSu/v3+pdGi/ePpOjbL9sKqoHy0RRqX9p4090T5St/P5ohSKWkpy5bhex4ZFSp99VRLao28qBblMSobXRlxhUkmPJpuAybFBgWfHyc5GQmepQ/+HwRt/t2ZpJWia/DX0hGS+yiZMgLRglyKULbjp8drw7M57/Oty4MRDZPeh+0hGqqy954dH9fO2Jw3dcbLjcDgcjoGKbq1CVTqiIgra/81ozcn598yXwU1NcvoOtTKpKY2FWzPBiFLSpv3pora8zG/JyrL2onQU6GVfO2OrY8OgJl2QbYbVysTGasmojlKC3JRfByy0lCyo3sLYKseGhJOdjYi7F9wkebOmRH+mkRvMf1lW3B2VaKhqkqFVQ2RMw0SpKdVLWp9V5PJVImTjchLyncfOlX3G7Sf7jzpUqU6NkiElOUlaj7LVSolS5PFxOBwOh2PgIWgUUmJiH0LAE/L4srz8/q5Zss3YoXLajnUyrEb7xASEBqUjJ/+d2SkPzsvL7GVZyedz2m9GhkVH7yCT6ZLDpg6TgyYNkYZSXkooNKVU5G2D7BDBItEPtzs2HJzsbETcNfdmJTv8HCazbugjL3sqscBAeJzs9Iwl7fNldtt0yemzm9a0k+w35mAZnhkjOchMIiFpJTbffOgzsu2I7eTIiW+VptQQJUFJySdy1mgwOxvEJ+meHYfD4XAMYEBiIidBQvvBnFz4UkHueWGRHLrlIDl2Wr3UEu1QyGn/mZabXs3L3a90yAGTqmXXMVXSWJWQlP3gqCsjvYWkkhk8OikzwjLLHDpKFNYG4UEP1Ffk2MBwsrMR0ZXt1A8Z5l5+3OUPOtr0ILbVob3UKrO6Zsi9M++QZe2LZfsRO8lxE07TJ4abXjNoOu/xL8m42nFy5PiTZFjdSCVAKckq2UlBdphyJkXooMfBOhwOh2OAQrs6qA79YpK/Qof86JGsvLy4XU7cdrC8RUlNpljQvjElzy1PyKUPzJb9thkt+41LSGMiL6VkRpVvBtK7Z6e3EE1svXJcMWN4GLDDM+epFzHgumdng8PJzsaEfskFfdSMB9TmqJv02KxjfPWOHlHK63MqJmROcbZcO+Nfsiy/TD6+3blSX6zXo/pQkyX52YvflZpctRw1/u0ybvAEbdCT2qAXnOw4HA6HY7NApMmhXaBHQ3ba5ct3r5CWXEJO33mY7DlCtG9cIfNKdfK3Rztk9py58v0TtpKMkSO0EBRxVG4fM9JrKPF2zI9j5JTQNUlky5tKghiT7K6dDQ64jmuAGwv6pFMpbVD0Q04l0sbeSawnEylPq0kJJS6pYkpGVA+Wg0YdJA25Onm17RUpFotSTDINdVEGpZpkWWm5LJGFSh61wdbPukrPtcA1JUORY9/hcDgcjoEJQqCKynjSwX6dSklrW0qqUkkZXFOSjO4vpBrlybkleWFem0wdPUhqVB9J8tt19oOWKe0rq01H8dRLKZnWxFLVFBQUwgYT1bqiz12fP3kcvQMnO47+jSolK5pqpFGmDNlWjp92stwy/Rp5rv1JxmHiI5ORjWMlm8/KsuwiyZrlJLJPMTGBNivKd3xyAofD4XAMXFj4merKBdWk7Yf5hWmmO2VKXVZG16Ukl0zJrTNzcuNTM2SbkUU5fa9R1keK9o/JYlp7Ui3BdW3HAIWTHUe/RlHy5sHBbJUpVcuImjHSLi3ywvJnpCPfrs1zShrSgyWlDXlrrkWyhaw22pEvx8IFWSsbuhwOh8PhGLig90vYWOAwEmR4TVLq8Pro0ScWdUqulJJdxzfJYCbuIYoKl5AFsvG/d5aOgQknO45+DZruaCpMGnBttEt1Mri2UWa2viILs/OtaW7KDJGqZFpWKNnJFbO6J8ofQXN4++1wOByOAY2oo7NhIMWShbQVU0lprEpKNTPB5vMyu7VLRjTVybbDayVZzGu+KH/RNMHyb744HAMQTnbWAOZviKe1QeU5jC+p3NcTKo+H88JybVAoFCytyzlrg1AvUl4bzY2FdKnaqEsuVTD+AuE5YMThkpUuuXXBtbK8sETGZsZLY3KwLGpfIK35Zs0f3XegO72F+DMJiWefzfKbBdq5xN4DS1LYx3H294RQVji3cp3kcDgcjtUj3l6uTXrxxRfl4YcftiVteE+g/Z49e7Y88sgj8tRTT/VYDqkvYCHbukxKXlLJorTQTWeqZNSwoZJIFGR+W1HSXW1y/PZNMrKKzrRKM7PUPkmz5nV1fX9QtPL+X6/vqtzPMqyvCSE/76GynPi+eKrEuuaJ16+n/T0dC8nRf+BkZy0RPtx1+YDDYLPKQWc9lVG5j+3Vnf96SCaTljb0QLd4/VKpjfebNdGYG70vBuhEO2R07XgZVTdG5i2fI/OyM6QmUS2NmUHaxOelrdBm2azRt7E6utaLX3n8ubAOieHZh/fQ1dVlHSf7wn6W4RlWvvcAGu7Ozk7p6OiQtra2Df4+HQ6HYyCDtnXx4sUyffp0IyikWbNmyYwZMyzNmzdPVqxYIblcztrYn/3sZ/KJT3zCls3NzdLe3m7HW1tbu9OSJUvk8ssvlw9+8IPyla98RVpaWixPPKH89gksHE2T3req4tLcXpLaVFKaapPCDzHMbemSyfVM9qPEpqD9lP7R+3BaFL7G7/2tfz8T+jKWob+Kr1eC/eE4S/q8tQH56UcDQvnxfZRF39vTu+Ba9K1r+54oP1wjjrC/p2Ph+o7+A596eg3o6fH09HHHwTmkIAgou+l02vYhkGEZR8jPMg4EMuRd03UB16Lxrqurs+21OWdtEOrFkmvU1NTYdm+DyxYT+XJssT7DREkb7qzcs+AOuXfWnbL12K3kyKEny60LrpcnWx+VQ8ceKXsO3U8bb31m1opH9aZh39CIvyvW6Ry//e1vy7bbbiuHHnqoDBs2zDrFrbfeWs455xxpaGiwfLxP3ivfBKSn8h1RzvXXXy/XXHON5Z8yZYp8+ctfXuWb2VDv1eFwOAYiAoH5xz/+IdXV1dZ+0m7S5tKuTps2TT70oQ9Z+5rJZORLX/qSPPTQQ7LrrrvKN7/5TbnwwgvlySefLJcWASUWwgOJokzOjYNyv/Wtb8nkyZPLezYi9No2MUEJaiPyyKKSXPtSq3xoz+HC9APXvLBMRtekZN/J9VKVTkq6pP2JxbEV9Sh6ifWa+oystHUC9x2WIQWDXiAxIU9A/F2Qh2VV1etPex3PC0KfiJGRdwgol20IDXpK2B9A3wtxRUeiDwaV/Sk6FIjvr6x/6LvZX5mP80n0+Y6+h74f/52dNYHHEz5mhOz++++3xhBBmTt3rixdurRbYMKjRLjGjx9vgssHf9lll8nxxx8vtbW1dox8ccU1IFwLa/4zzzwju+22m+VD6Z0wYYLssssu5ZwRwvXigvbxj39cFi1aJD/+8Y9l7Nix3XlAyPf0009bnRH6+LkBTU1NMmLECMtDg8E9hLpR9kUXXSSf/exnbZvzWYZ7i6OnstcVhVJBy9HnVdRnrO1yMcW0A0VZUWyW65+/Qp4vPC5fmfYjeaT5Qblh7pWy89Cd5fjxpykx0mvrrZcgO1q/ZLJ3vFHcOw3rzJkz5Ve/+pXce++9Ul9f3002+UZoFBsbG20fz4QGePny5UZgDjjgANsX3gVlvf3tb7fyKIf9vIM//OEPstNOO3V3IHFsiOfscDgcAwn0W5CVl19+WX73u9+Z1+WEE04wYxSgHX7sscfkn//8p+yzzz5miWeb/h2j1cKFC2XZsmWWNwBD30033WSJPhLvTrz9pT+g344ruaGf7HVoV1cgJQpGWq59rl0WtbfJu3YZKY/Ozcq/n1osnzhwnIyt1YNaHbMDloo2XkdrqH1sIuo317OrpK8ioRP97W9/k7e97W0ybtw4I43oNLwPngN6Akv0k2OPPdb6tzlz5lhfefDBB5dLi8qjPwTkZ5t3ePXVV5tHjecadC+A3nLUUUfJkCFD5L777jM95VOf+pTpTvHnzzvF+PiZz3zG3jvXCESYurH+29/+1uoL4u8vvn7IIYfYt0T9H3zwQSPXAD3x+eefl8cff1xOO011kdi16e+DbgDixxy9B33OidT/KcrbjjUAYfvpT39qlp2tttrKFNvbb7/dBIuP/dVXX5XnnntO5s+fL1tuuaV91AgHx3fYYQdrXPm4KQcXenCNI7gow4D8NNB/+ctfzCOAcF955ZUmOFtssYUpyViVEESUYcrjHMqksQgNy4IFC6zRhnCFPCFBhIIwEnf8xBNP2DVDokGfOHGiNST/+9//5LbbblvlONYvBJv1cO6gQYOskeFagGVYfyPAHY83J1nSFrhMXlLaKKelSpZmF8qMjlfl4NFHyIpcm7zQ+rRUVadll8Y9aLr5fS7z59i5r+WWGwyERvz1r3+1b2GbbbaRww47zJakRx991N47jeq+++5r3w0WRd7t7rvvLoMHD+5+L8Gjw/vmWR5xxBEyadIk6wieffZZ6xxGjx7thMfhcDjWAJTWUaNGWV9M+4wie/rpp1sbTF9Ke0rbTT9If0efSt9NG0sbPnToUNtH20xfSKKdhTy98MIL1v/SRodjlE+fj3INyEu/vKH6wjVDO0i9DF1dl/aRD83JyYj6nIxpqpFH5xVk9pIuOWK7Jqnhd17ISJ0SzMKGR6dcx/XsJ3lG4T7xeNGHYbDDQItexHNgPBRLvF48O/o4njskEx0IEsL7Ig86CHrMxRdfbOOjgt6x8847m+7E837ppZes/0T3oI+F7PC+KBeiim6z9957y3/+8x8rg744JAy+XIMyOEainiNHjjSiyrgtdCeMuJRNqlznPojegOxwPiSPPhydDh0NHYxviW30JUIjIUdBJwMb57twfEPhnp01gMcTHhFCeOONN1r62Mc+ZkonHzVWHkjJMcccY4KOINCYsg9i9O9//9ssGDSEQcix6ofGAcsC7nYsAnhO/vjHP5ow0lAgWDTGHIMwcU0aAdaxUoW6IVhYU3Cr0wBQHg32Rz/6UTserkX+O++80xoL1nsSNixWCDKNN6QIEhWeA/eDp+m9731vOXf0jLbffntrqEJ54XpvFIVS3shOupixtpxpqBMFvQ8lPU+1PizXz7xazpn2KVmSXSpXzrxUajNVcvaUT9sPkhYgSdisYD29RHa495///Ofy97//3bYhJzyLQEiwQtG47bjjjmbl4j3SuO+xxx7y1re+1b4pOmXiymmU+Zb4Hk4++WSzjLF+6aWXyiWXXGIdAx5COlga0fjz3RDP2uFwOAYKQp+FsYi2FoMibXPom7Cyo2D/6U9/MmMUCimeHfrdH/zgB3beb37zGyM3AZRH/4uCSxnBwEe7TjuOsoxHIeQF4Xq9jlJR+0u9ZyUwzVmRvz+8VPbeIiPjm2rlkkeaZXFbQb5xxCip7oWqhGdN4l4hg4yR2m+//awvfOWVV0w/Oeigg2wf+gdAf0I/Ii+EBwLKc9xzzz1Nh8K4jF7Bvv/+97/Wn9In8g4uuOACed/73mc6FeAdXHvttfZe0VvokxmDBekJ+g6AkGBMPvroo40IUx5AP8NADHkK4204h2uHe+Ne6LMB6xyjbMgReiHbgPvhGeD9oXx0Kco95ZRTLD/PKDwrR+9Dn7N7dtYG4YNkiTKLxR5lk4aOxu2BBx4wa86b3/xmGTNmjLF9PnCs9Agygoew4yFhYCSCfMcdd5iln9AkCM6BBx5oFgDii2+99VZrFDiOJQDPEPkQYq4PocEzgJAjXCjKv/jFL8y6gNuWPAgW4XNvetObzEJFQwCwfFA/6k2iIQnrIWEhCY0RZOuqq64yzxXeBYSaToBGCkJGR8D1aTiCEMef1xsHMcXKVfDO6BKSg6vdyq4qyYzF02Vw9VCpyzTIrBUzpC3bIvsMP0DzagOlWbrz6r/eAu/2lltusQaNa/HusfLQkfJuAfvpTNnPPggl3wG44YYbrMOlMecbeOc732nPE+IMUeJ9XnHFFXaMhptnznvleHjGYelwOByOCLTFhJ7TxhIVgfWe9hOjHaHmtKFY+lmPe3YYc0l7i0cBxZp2mEQbTz6UYZRd+tJwjLLodzF6xtvljdc2MytYUYqJlCzrLMr9M1tl3y0GSUs2If+d1SGNNUk5aHJdr3WF3CcKPP0hzxMiwXO/+eabjUTimeE4+gNRMXh6gjcsPE+iHtCTMBjjgaNMiCokBKNveLaQCYgNeg3vk4QxkWtjFOT98u4gsZTFN8B7pP/lGEQEPYfz2eZd089i5KUeJPSZsIyvx5ckdDDeP0ZhrsV3gNcIT04wWHMtvhWeSfybCEtH78I9O2sBWDwfJEuEAk/Jpz/9aSMbCBgNHwQF5RQLPIKGx4UPG+FDiIkXfv/7328K6z333CPnnXeehZudccYZJggQIgQaYUZ47r77bhMmCA9E5Wtf+5qFPGElANSHsr///e9bmBmkh0Zj+PDhdjyAV4vCjSBvt912NhiTOkJOKANBZ4mw0imwzvW5V4Sea+IFopEgL/dKmQg1hCsQKM5BqE888URr7NmmLNIbhl6PPwtLYzMReXaYITOfzspTCx+TJ1selcOnHiePzXlYHl54j3x2529IMoWrmPBj/Y9z1jcQeQ3geWApgsD85Cc/sXdIwxbuHZc7wNtGQ0h+niexxXxHWLPw1tBY8k75pvhm4s+Odc6jEYVU09B/4QtfsA6Z986xYFFyOBwOR2TBx8vy+9//3iYfeMtb3mKKNX0w24zLoS/sybPDMcZ00BbTvgawDmki0c/R34f9oc+jPacvpL2mfQbx9ry3ENWTwO+E3De3Uy55ulW+f/BwufSpVrlbt0/doV6OmlhPZaITNiDizwhdAn0G/QZygp7wyU9+Us4++2wjFPST6A94ZQB6BSQFXWX//fe3fhGvDtEwhMkffvjhpg+de+65pjtBloimIFqCsETIKv0hxIqoE8b9YGAmBA7PDjoW54d3xLv74he/aJMH7bXXXtYf8y4hKBiw6cPR6QD9OlEzU6dONW8eJAkjJeXQ5/JNYbiEWPH9YACGUBM+x7fBPgzcnE8fz3fG9xX6a++3Nw70fblnZ20QhARlFe8J3g28LJALlFOID4onx7HOf+ADHzClnw+ZxhKrAkLFeB5ihAkvQ6D46GkM8ZgQi4pXhcYYqweJ/HhUEDAEjkkL8PIgUDQGEJGTTjpJ3vOe95iQBstEPOElgOjQ8HIN6kO9Ub5DjCoCSKNCHhoKXMmUj1cJIcXagtJOY4SFhYYcjxBWEsICCKviGVAWAs2zIm0QmGeGhrRcnq5DfCg/mUxITXWN3LvwLpk0bEtrrGa3vSp7jNhX0smI7CT1/HBObwFyyLXpRFnnOUNcSDS6PBOeJe8Bzx+JbZ4ZDTHnvPvd77ZvikYZi1YY8xMS5/IePvKRj9j74j3wrYRnvcGet8PhcAwAYBQiDAplln4WDwN9G0ZHxmp8+MMfNiW7J88OhkXG+aAYE46O0oqlHoMnfWgACjDHSeTFeEXbTiQG10QH2FhtM9NGQ3UgPE8t7JQnF2Vlv4l1cscr7SLplOw3RmR0A+OGo/wbEvF7ZJ17p4/C8Ee/yHOHANBn8XwJy0YPom9Ev4JU0A9izIO0oEvgBQlEg+dIiDfvhSgKdDB0FXQe8hNpQtg3uhT50VV4r1zzu9/9ro2nDQkCzHskL1E5RNLgTcLIjN5GmN1xxx1nBklCH3nvEC2GDqBzXXbZZWbcJvGuITUcowy+E0geUT7oSERi8L1g7OZ+Q5he6LM31rexuQPPjpOdtUD8w0QAachQUvm4EZx3vOMd1tBBXhgYxzpCQx4aWggKAgT7xyrRE9lBWILSjIDg0SG0DSWXBpnjWD1QfGmYOQ+rBsexSgSiA0mJJxoblGpmiKGhQZFGGUfhZgAh4VDM/gVJ496YpYR6cR0IFAo79cHlDGHDY0WHwH1QB/aF/SjqARtWiMtl6SKUqm/D/q9OVcudC26RkbVjpC5Za2Rnx2G7SXWi1sgQzX9Uld4jO1iueM8QVAgj75p3xDOmcYQEYw3iubKP90LHSqJRhzDS+NJAY/GqfIe8VxpU3jH5+LZYD98k2LDP2+FwODZt0J/St9JP0S4TBUEbTf+FAsu4W/q2QHboe1GuUVLpo2lj6XPpI4myoN3FAImCHizyn//85629p39G0aUcxmXQrtMfxtvo3gY0p6h/eV15ZF5WXlnSITuMbZB7Xlou4wbXyD7j0tJkxsgo/4ZE3LPDOs+Ofo8xNoytYZZYxrQQZQIB4RnjeUG/QM+AmPKO6B8J/w/9JPpUIDuQEvQSxjQT4s857GdsDuSEd4BhmP4S8oRRmHfH+NcjjzzSjLKchwESUoVH5kc/+pHpWZAajqMnBYMt/TrfD9eBvFB3iNaZZ55ZvtOV4HtCH0S/4huBUGOoxrPFvUCKWcZ1JOD99sYBZMd9aGtA+BgRYBLTVCJQuEsRBogCCi1uT0gNHzceDxpQPnA8IggegoxbHeGMNwwBNMx4WrBecBzPC/s4F6HHZYuwIVRYkVCMaUwQXMbp0HBAWLBOxBPuWmJlUawpL9wP5aI4Q1ICuJ9QN5bUlTojoKzTeCD4nINQo4DTWGC14F7j99XTPa4PCFvT/23dHDyaiomCFJJ5uI5NSZ3L5+SFpXRqVfbjossKi43akGzqaSNGvQfILQ0c7wjCyDvnOZF43jwrSCfkkn24tWnEWedb4Z0SakHYxOc+9zlz1VcmnjPHcPETdhF/Tw6Hw+FYFRgMCfVmYPzXv/51Cy+nD4XsEEIVwq3p21iGvpEl7SqKMgoqUQ8//OEPzRuBoo4Cj7cAKz2zjjHYnRlOidrgmijnEKxQ3sYCP7yd0jR7hcj01owMSxXkJiU6iXRC9hqZktENdeVOtHfAM0PHINGX8Tww8hFKBhGkz0MnOf/88y0vRmLIDs8fnQoCgheEMDhC8+PvI7wTdA/s8xAOwtC++tWvWigZES7kqYx2CP0j0TX0o5zzve99T375y18ayaEcQhohZ0ROYKDmPO6BvhkjL8cgRpXACE29qS99Pt8V3wp6GaQKvQ2djnLQEYnKoFxH38DJzhoQhAWwzgdOQ0bDiVcFcoJwANypEALGtGAZgiQgAMFSAOGggV0dOA5pQKARdsbyYBXBYoAyjIucxpoE4QnA4kQIFOFluHLjCYtFaIAA94Bwomiz5FrsI4X7oP7MDEY8Mw0RXigacYQXpR1Sxbk0LO9617vMlRuvz4bFqo2zNmG2NHc9Dbf+a6xvkuau5dJV6JS66lppzbdEx6OMmnq30yG0kc6QAZM8G6w/fBcknjvPkX2EUZD4TnCn03nSOJKH74L3j3WK326IJxp0Zu/j+cffk8PhcDhWj+BdoT/DGIkHnjY2zIrFrJiEsxGSFG9XaWcJY4PEXHfdddb3YrCkX8YTgRKPxwDPEEo93gSiIvBg0N8HhL51Y4AohqT2e63ZkjR3FGRYfbXMXb5CqquU6AziR8C5v96rS/w+MdaiM0AU8HJAItAZ0FUIx6e/Y+IjninGQp4hugV9IEZX9gN0EXQqdBAMvOThWXMtzoGgENqGnkLi3YaJm+hXycfMtOhSkFM8N0EHwzjJuGRIGO8UvQ5wDucS6ghZwVgZf6cBTDJFHx+8NvymDh4mEvXCoMz1uG++MULVve/uOzjZWQsEoWGJMOKqhkRg4WGdfSj+7CNUDXc5Lkw+cjwvCD7n4yYPgkYjSewnniLiRhFOQpggLAzuwzWOwCM4NBi40bkGjTLeJMYIxQWHhpuyKxPlcu2QlyWWBuJoaTSwrLCPRCMDcOVjiYCoUQZCTCgcbl4GC3I/1IcGiIblrLPOskYoXp8Nh9d+oknRexPcwXo9fZyja8Yo2WmRZaXlUptukOVdi7TJL+j7ilz7vU12eO88SxKNHlYsCA5WH549jR4xxjTcNJp4f3juJJ4fCM+fRpcww8pE/DN5KY/kcDgcjtUj9Ecos/S19GeET2FhDyFFGJBCuDgedkCfCVDGUbTpxxkfwlhX2mj6T8bq0q5TBnoB59KPs5/8oHf6w9eD9iGSkZZ8UvvArDQ11klHISOjagraRxLgpjlKZSNgLyDcL4ZPvDT8Xg16BMZZiAT9FuN12M9EEBj60IPoK4l6oG9El0JPwjsC8AT9+c9/NuIJ+QjXICqFaBo8OuhHQdfhuoEohX6S/YyjhuByHN0M4yQeHsIU0V++8Y1vmLeHa/A+ebdM5sT3EiYkCOWxTuI7oK58A3wbGDI5D10JXQ49CWMyOiE/Cs61w7fl2Pjw2djWAB5PSAgYLnFc4OGxYS3CasA4HrwcCC4WAxo/xvMgPKeeeqrlIxaVGUmIH2U2NtYRGlzhzOBy+eWX2zpCgtUIYkE4HL/MjyBiAUEAaUAQGqxVCBKztWFFIVW+TtyrzCCHskxjQmOMixlPAUJMOdSB3xWgjoSkUU/Keu9732veB8gbcbIQJIgQSxofzuN+mbkGDwQdB+VRh1DuxsCzzY/L1TOukEGNg2Ry7SSZ3zZX3j7xTKkq1Ukxk5OqYtV6/yr0msC9hqlNgwWKBhLSyncCQaShhbDwDGloachpoGkQaazpeHHN4xWioaQBjoPnSCLmGWsWnTNTjYf9IY/D4XA4IkBMCENCqaV9hORgRKRvQkEFKN3f+ta3rB9D0cagRLgw7TL9HG007TlEhhBiwqxQhjFw0fYTzs7gePp6+mUUfaIwaO9D+7zR2uZSQZZ0FuXqlzvkvhkr5MDth8l/n1ogJ+00XA4aVy25EmNclewkVh03siHAsyDxbMKU0jwDgM6A1yuMCSbML+RHtyAsm0H9/KYRz5L+DX0C3QUyRH8ImfnOd75jUQ7oTjxrwuPQYSiHdwrJxKjIe2IdQzHl0t/yviEmhPTTx+JhYh/l8p2EurOPcV3oWdSBsVdBp8GDw4QXEDD2Y6xEX6KefAfUDW8P98O1+Nb4liifc/ECERHENQO839440OeccLKzBiAAgA8WAoMw4foOAoJnBosRZAV3J2A/+whBw00KEYJM4AWiweUDxwpAXCeNJiSDdRoJGkuEBLcv5aDcQj5QnBE6BAXhggQxWwgWEQbu4coN02DGwVgeXKkQEcgOxIjZ22h4AGUCLBK//e1v7fpYI7gf6osSz+A8gLIO4SNsDaLGs6GOPBcaieDdIXEslN3bWNKxSC6bfqG0JZtlh0E7yXPLn5d3TfmwDEsPlnwyJxl+kDTVO40K94+FiXAH1pkukwTh5V3hgeN5QxyxMNJIQ14Jp6DRJfYbSxQNOQ0xz41vKw7K5ZlSHku+FcbwgI31jB0Oh2NTQuijMUZBYmiTQbzNZKIdvD4o5PS59O1ET4Q8tMck+jcUW4CFnrabCWfo8zkGUWIwO8ouIUuhreb6G62NLuVlTltBLn6iWRZ1FGXbCcPlpVkL5D27j5StmvD6pCTDGNjEhrf8cZ+Ae+a5kyA8kA6OoSOgH6CDhOOso28QUg8BYp386B9Bh2A7eGrCxE+EFMbzAa5B4hw8LrxLPEjheBzh+hwLoWu8v1BnCBdjdHhvlEk+UrhHwumI3ggzqwGOUSfycX3efyBUgPLDteLoqX6ODQ99zk521oTweFiS4gLQExC2kAeFlo8eYX29cypBGSB+rbAM5QewPzQoPQFhIz/ncT6kBkEmf7yccI2AcL04wnH2x/PTSHCflag8v7fQ2t4iNy2+Up5reVx2HLKrPLHoGTl1y/fJ1NopUkzko5C3ZO/UhXun4SMuGAtSmHY8vCdCDvHsMX4qPHPG62ApxILFNNKQoF//+tdmZaRBDC78AM4jYVUkMfsdViSwsZ6xw+FwbEqgzaR9BqF/Yl9l/7U6hD4ztLGEJYfQpHh/F8oMCNvxa20UKNl5obkof31kqVSlEzJq+FBpX7ZEztp7pAxKFrQvZNIErZON3dmwWNOzXBdQFv1kKDMQk7i+sjrEdZH4ewjlVepPIOSrRHx/KCeO+DbXRddiX7zuYbm68tfmnhxvHPr8neysDSofER9uaAjjx8KHG47FEfLF98fPDWWRehLW+BLErxGWqwPnrQ7xcykThOtwP/HrxMsJAh2vUyXWVK8Nha7OTnloxd1y++wbZMvh28izC16QI6acIG8a9Ga9Ka1zWuvYS3Fs4RkEYou1CoR7J2yQzpGxOOH5cQzSEogoZBXCw8x3nB/G8VQCy1cItSD0DWysZ+xwOBybKkLbGxDazdB+x8ExUk/7e8of7wvj2wG91UaHa4Tyi6WiPLwgJ/94YrkMrUtIdW29jKvKyju2b5REsSClVLXm1fyWu3dQ+WwA+8IzDduVqDzGdjgvjp7OBfF8PZ1Xifh1QGW5lftXly+A4/HrVp6HHsV3ASqPOXof+qyd7Dg2fRTzRVmcnyM3zrxa5nXMk7wSnJFNw+WdU86SmkKDFNNFpTq9Q3YcDofD4ehrLC+IXPHcMnno1U6ZNGqQzF+yRM49ZLwMT3RJKZFB49N/yV4lOw5HfwRcx31ojk0e/JZOXbpRhlWPkmwhLxn9rFs7lkq7tOhXzj//zB0Oh8MxcLEiK7KkraT9n0hbV0G68iVpMhtfSslO0iadTrht27GZwrVAxyYP4pCrk3UyvH60ZDLVkkmnpbOzQ5Z0LdQvPKENvNuyHA6HwzFw0dJRkCXtRamtzkhHriSd2S6xoOpEQoqavBt0bM7YrMPYuqecT9ivstgqv+GCo7cUfnzLG4g+hX2e/GyBmaX0n1mqdCVsayPeJZ1Sna+RpfmFcuuC62R+bqHMbZkhe4zYQ46ZcLJUlxo1Y1Eb/KIkSyld1febLEkhEf0eAvuS7uR0OBwORz9FUfvCpGS160trf8a4IF2YEpOTXKlKrnq2WW6elZNMdULaOnKy1+gqOWe3IXpM+zc7l7GrBT0VpSbScJi+hxLK3Sk+oPKao6+A9403VSLsULfRTFjyG+q8Htvv6so6gTC2zZvslG+d/y2SlRUkn1VVhvkZLhf7vgVCn9fGXLSR1pei70nZjr4bmgG2+L9YKth6R6ld/rfoDnl08YOSLXXK8MQoOWmb02V4abQUU8xGo2RHz08U9K1qYwHZsXIgQNqAOBwOh8PRH1FQfSWlvaHRlgQERjUU1VkS2q/l8kX57b0L5Pm2OqnOVEmuo1WO2XGoHDFJ+0fr9VSfwbtTTBvx0W7P9J2ClqenSkETZdGzagcZXdDRNyipvpNI6ztOm35Sn9Y3zvuyl827V23H9ZV1gpMdbSzg0PyPbydXRKnWB4O/l2/JvqfN9vH0CwQikta/RFEZSjGhxEUb/KS2zrrf/HAFbQCS2mwr6Xmx9QW5ZuYlksxkJNdWkrdNO0W2qd5BChk6iTJJ0jJ5t7zzBARKE+TH4XA4HI7+iIL2X0ZU0FeM7BCZoGRGld9ivku+edt8WVKo04xJGV2Vk7fvNVS2bdR+L0XPp3SnxNTIEJ6kdOmZzR0Fmd6cldZsQjpyCSM9zBqG58DRh0jkVDfh93kSkil1yb4TqmVEQ7XuQVMFKUn7O1onbPZkxxwG+s10ptrk349dLnNyM6StvtXchaliStOG/6Vhx7qhkMxbiFkynZSqVJU0pQbJ3o0HyqRBW0hjpkmFXzsAbdy15eeL1g6hKD984qtSqC5KVyEnO1bvLMdNOUmqk7XaiPO6QyMRffaQHVt1suNwOByOfgpMskQ30IPZ+JsSHhglKYWidOj+z9y4UAoZVZCV3Lxjm3rZbyxTTWekSrPpmdKm/eNlT62QV5e1S3Mn/WNRdhzXJMOqC9qXKh1Kav+ZRO/RzI4+RBTCRpxilRLancfUypCaDLS2/O7ds7OucLJDI5AoSj7RJS81vyALOhZIPtXZbe1PKuFx9C2yiU7pyHXIss6l0pxbLisKLVKTqpVxVRNkx2G7ytTBW0tNvl4bAKU96YK+0oL87qmfy9LEYm0YijKiMFaO3f5tMj45uVyignZE37utOtlxOBwORz9HCU9OIm39FX0bqi9LSM/0jpR8745lqtQVZMIgkVN2GCKTG/nBhYKNUV2US8k9s9vktuc7pE7ZzJTh9bLbpGqZ0pSWmnSi21NghEqVaUffAXUkUBlsuBl9HcGjBwGyg0pKHWuPzZ7sRGFsBVOUCYcs8sNbyHr41JD5zfbp9A+U8vpukkpIpUvaS+2yID9Xbpl5naxob5M6aZAthk2VEyaeImm8cCneZUGunXmtPLjkbqmpSUqmq1H2nXSQvLnpoJXvEn5DGBxvOkxRE1oXh8PhcDj6G0o57d8IR2Okal41l4xIoVP13pTcPjchlz3RIlWFnBw8OSOHbD1E6vRwstQqr7bXyH+ea5cXF66QPYZl5E1bDpIxDVXSlOmyYKliokopTqQ82wQF7jXoU+Cvi95G5MkplJhaArWlZFFHRnCd7KwTNnuyE5Rf8wrYhjYiRf28whNhtewBcPQNeDd4X7pJib4O3lUu1SWvtL8oj85+UOZ2zpHdRu4luw3bSxqSTZJNdskVMy6Rx9sekCqpkbHJyXLGNmdLValG368yHW0n9NOPylMUlSDZxAcOh8PhcPRDmNel2yqnSor2iagqL64oyq/unC3JdEr2nlgnh281VAanirIiW5Rv3L5QWpJp2WV4Ro6c0iBTG7Q/ZbS7KstRqBQl8rdS6QldraNvEJEd3nXQPbG6864Yc6xHTSettiOOtYOTnXLbQSNSKBOeVAhrKj8VbCiOvkMhlbNwQlzx1iTr6ygm8vrGikaA2jrb5fwXzzPvz/ZNu8rOo/aQSekt5PmOp+TSGX/V11iQIZ3D5YzdPigNMsjGYiVSUVn2jnXhZMfhcDgc/RmoK5GOQq+mPVgpL13aL17xTLPcMr1DpgyrlpO2qZGxQ2plwYq83PNyuzyypCj7jEnJIVMaZURtSvtSLaNMZphxlj402ow6Q9Rp+lZHXyJ6I2Utxd5I9H54+xEZdX1l3eBkJ3bnjN3hU4qDLaJeHX0HZkwDSWuUI3duPpG1dSMu2tjf3XKjPLzoflnR1S7jGibJaWPeJ8kqkctn/01eXPakVBeq5dRtz5JxNRMkyQ/1aGNh3iL7YyrHMut1rDPsGVrvGT1D3g+b8X3azOjS4XAMdESKctSyopLTIFjEMNt4FLSt7fbSO9YJRWLsjaAY5RFUtxeXZOWChxZIc2KwHL5Ng+w1LCEzl3TKf2d1yQstRXnrDo2y/7iMNOpLKCS0z6Tf08dv01BrmeYzoNzyFsq0eQ8cfQfrQJGRICfWq9o+AtvYcq103eBkxzEg0FnokBeXPysPLf+fzG6fIQcOPlImDpsk7aUVctvMG2VJ1wJ5y4ijZbdRe0l1oiZqTBQ2EYV2AITKWQviWGcEImMdcIqGOFJ2eKD24616PGk/EuBwOAY6oh/nZopk1u0XYdCsJattbl63ciknO+uNgj5R1XKL2l+ldGXZioRc+8xieXRpQVKJKjl0WoMsWdouMxd1SYc+43HD0/LxPYdItZIZpqrGnMuYnAQGP4djM4KTHceAgM1SU2IW+qK05FvkPzMvlOVLlkmhWJL00JQ0F3W9kJPRVeNkUuMUSeerMEGqIl6UQpLuuaids08zvj6A3oyoGyOjBo+RMcnxki5mdA+/1VDQBkbJZCElibQrNw7H5oCCahPmHygVZHEuKf99tU0em7dMlrfzc5h1kky2qeLtoeHrg6pCXrKJen267VKd6JAViWHSqUSyWp95tXTIhMYm2XJsRrYfkZTxdUmpUcKTTurbKEfm0wpbS1w2UDkcmwuc7DgGBPiE7ee2dMmU4cuLi2X6opfl+bZn5KUVL0hnskOqJCWFdN5SMpexVr+YzNtvKaGQ+3Sb64uUVOkzH1wcItOGbCc7jNxNRlaPiXpXQ1ESKbckOhybAwiAImW0Lf7L4y3y4LxOJUB4dYqSzydUYW+VQsIHV68PLNA+WaVdl/ZhpQ7JSqNk0tWSThSkJlWScw8YJkNTBalKdirhzEghWW3hTvzgNuFpRDQQtu2OdsfmBic7a4n4I9JHVl57LSofZWVejod9r1fmur4Szl/TtTck4vcRsDGvX4lCqaiERa/HuKtkVhc1kk/kpUWWy+zO6XLfvLuleWmzhavlq5i+k1AA7TCKjPvJ2LLgv6S2Xkjos2uvaraQtVQpLWNkouw98gAlPTsZ8RQllPywncPhGHgIfUFY5lWtTmp7DMH54HXzRVLV0ljskrGDUjJhRIMMSvOL/1Xlsx3rgpw+30RR+zqC0RiDU+iSB15qlvlKahKFrLx/u1rZe1yTpLXNtR8cLWQkx4+MJjr0bG2DS1E73Ft9c6UO0BPi1w75e6pPT2WF72xtsTb3Gb7bSqztddb1fsKx18vr2PDQ5+xkZ02ofDz5fF6K2uCkUilLrBcKBUmn090f7iuvvCIjRoyQxsbG7uMcI0/ArFmzpL6+XoYMGbKKACRxO+uS81hyrLOzU6qr+TXklcJOvnAeCPspt6urS6ZOnfqaPAHZbLa81jM4j3sDof4B3P/ixYtl9OjR5T0RyM+1Qh3D+kYBbXtSn5l2ACjY/CpPc3aZXPfylfJS5/NSzORl50G7y/4jD5HhmdGSTXTZaRlt/PXulBjltICNVNcBBn51uznfIq80vyLPLn9SZnW+Itlihxw+5hjZeehe0iiDbfY7h8MxMBH6HmvvCzl5qSshf31grrbBSdl/UoMcukWTDE5rH2L9Qaee4J6d9QEh10wwUMKIxDjTYl66lOhc/2y73PLyEiU2tTKhNisnbjlMthlRo9wmIdBKxlMKfVwCKlor+Hc2NPgGQr8P0EFmzJghEydONN0ll8uZ3lBTUyMNDQ2WF30IXQMdgwTYDsvm5mbTkYJuxTnkY3/IHxDKa2pqsnPRwf73v//JYYcdJiNHjiznitDR0SF//vOf5ZhjjpEpU6Z0l8U1OJeyli5d+pprVAL9jnsDoW6UgY708ssvy5NPPiknn3yyHQ/3Ge4vIDwvR+9Cn7OTnTUhPJ6wfP75501YamtrZauttpLZs2fLsmXLZOzYsTJ8+HD7eM8991z7yHfccUeZO3eutLS0mFBMnjzZzuOj/+IXvygHHXSQHH744d3EAnAMcvPUU0/JLrvsYsJx3XXXybhx42SnnXayPNQlkC3WuSZLzv3MZz4jixYtkh/84Acyfvz4HoXpgQcekExGFf2ycFZi6NChdj/koe7cb8hHI/CPf/xDzjnnHNsOoJGhIQt1YdlT2b0CJTtFJTsFm0I6Ia2FhXLb7BvkodZHJFWVkVRXRt635dkyvnoyLh3jNbxNBtHS8OPlSfiYnfVCIZmXNL/ZkCvJ/OIceWjBffJc8zOSSWbk8LFHybRB20s65cqNwzGQEfrHdm1fr3phmVw3o0v2HJKUt+86QkZBdKytTZrCnnRP73ohVypYODZzsfG0mX46LTlp7UzLL+9bIMvS1dpXt8iOjSk5cvuRMqYxLRnC1nj2zLim/WNR2+XeCNgO7z8s0ZMgFJ/+9KfN8PvSSy/Jv//9b9ljjz1khx12sDyBLCxcuND0CvQFCMuoUaOM5Fx77bVGVlgPegX5rrjiCmlra+s2IqMHocsMHjzYCAz6y7333isXXnihXR9dJg50mg9+8IPy+c9/XnbffXc7F6BrocOwPP/881cxCofrx4Hutt1225l+dN9998mKFSssH2TnhRdekMcee0xOP/10O48yWR588MFSV1dn55OX5Oh96HNOpP5PUd52rAYIAx8qwvWb3/zGvCcQkEMOOUQuueQSIw9g0KBB8uyzz8qtt95qRAdB/uc//yn333+/3HXXXbYPQURgf/rTn3YTJpaB8XMdLAII6pZbbmkCxLUef/xx2WKLLYxYcT4CRWOBsHAOCeL1t7/9zYQPkkXDgvBWgmtPnz5dnn76aWuUnnvuuVUS9zlp0iRrRLCO3HHHHZYXAvbEE0/Y/XAN9pGeeeYZu69hw4aVr7BxBTn6nZxoKmmmEH9k4UPy4OL7pKYpI9WFjDQUGuTAsUoqtaG3zpZnndJnRugaj11T9ENr0bqndUgKe80qIw2JwTK8bqR0Fjvl1bZXpKWtWcYMGS2NqcEb7VtwOBwbF/Q9Ac+0itzzzGJpT9TJSdsNkS0btJ21PgrrPFPBpJTskN/TuqZMkZ9cSBlxwVuDgS9V6pSqTEY69fnO7ChJQ3WVzGxp131J2WJQlVRrX0fLG82AR/ibruvahkZo30O/jw6EJ2evvfaS1tZWuemmm+See+4xD8+LL75oetKcOXNMx4EooGOge9x8881GjkgXX3yxkQP0L85D5wHoQOhWeG+IMMFzgy6EDtLe3m5LCBTX2GeffeTyyy834hFP1IG8lPHoo4/KI488Iq+++qoRLcpCPwpeKMhWTwnjNddCF0Iv4j7xaFEudcTojJGafeRh/7Rp06zu8efl6H18Q+GenTWAxxMnO3/84x/llFNOMcsA6z/+8Y/NA4Mw4rKF3EBG3vOe95hF4dJLLzVSdMMNN8gXvvAFE+w//OEP8rvf/c6EDnKCQJ599tnmnmX76quvlqOPPtrICh6Tn/zkJ+bVefOb31yulZiQI0gIC4L5+9//3ogLJAkhvf76661+P//5z7tdteSNh6SBSmEL+cJ+GhjIEQ0Tx/A6cT0sGmwHSwiepEDYKsvsbRQLRfMwEMLWWlgmP3vyh7L9iN2kI9cqC5fOkYO3OFR2HfYmbfC14bdGX1Fe2LTTio1b44EDQsMJH8SrliiltENOSaGUl788f77Mz82RQrogx048UXZr2Dd61rwDPS/L5BC6aT/iC2sqEyeHw9FPoUo2/WApGUUi2I8d0jcmUMAL8vSyhFz19HJ5eUVR6qVVfnrkFtomY30vSl77hFIiKWltf/HwONYd/PC5PXPIjm5nme1S/1I5JiuolS/fvFCmjWvSd9Ehj81sl10njpQzd+bXjqqlqqjnosukefobvrcLelJYR5/5xCc+YfoM+geKPh6VCRMmyM477ywXXXSRfP/73zdDbzgHQvCxj31MzjzzTNMxbrzxRnnb294mS5YskbvvvtvO++xnP2s6DCTlZz/7mRx11FEWgQLe9KY3Gck64IADzLMCWfr4xz9uBuM777zTrsW56DAYkNG7iH5hHx4l9Lhdd93VyAj1QY9hCXrSaTgW8qHzoXOxTnnoSxiH8TShG1ZVVdmQhSOOOKJ8doSNrSttrtDn7FNQrQ3CBw9Q/hGWuGDD3PnASYAPOAgCwB2K6xZX7g9/+EM59NBDzSKw3377yYc//GETUDw3uHmDZYPtW265Ra655hqzUuA9QfghTXiJKJs6YC3BOUeDQAgbVgmE/8gjj5Rvfetb8rWvfc3KpI4ghL+FBEGJJ4Q+vp+ycMWeddZZVleWeKNYf9/73iennXaafOADH7C8AfF73zjQBlwvV5K8vLL0JRlaN0zGDBspC5vnSVPtEJkweApdQtSwUE0SbYwmul7+und4WreUwtao3wsJMqPPNplIy3bDd9QOtoYRUfLIrAc1L9D8nGbQb8Qslt07HA7HJgJr3QmNUkSqt8j0pW2ysD0viWJBJg6p170ogtogIPamamgbTEb+87TuiYWSxaj7Ygctr64lCf8qWUjbss68TB5WKyMbquWZ2cu0ecaXVtD+mLcBzem9fjnoAOgl8+bNM12CdcLL0BGOPfZY+e9//ysf+tCHTP8JRAfQN0MyKAN9Bz0Hj81xxx0nu+22m+UnbAxQJl4broHuhHH4m9/8pnlm0F1A0D9YUg90tuBhgXygq7FENyMF/Qjg9cFoTUInu/LKK+Vf//qXbbN+2WWX2TaJyBaM1nimuA4eH7xB3A/lsiTiJQwJwHtF/Te+juRwz84awOMJHycC8qc//cnG4yC8xKT+4he/MK8Lxwj9QhAgHhAEPC9s4+HBuvHLX/7SyAjeGoQAAUDgCE9jiZWCcvD+IBhYHmgo8OxAlvDsUA+sBLhD8SpBfCBHCBmWA0CDgaBRPg3HggULrI5YTRhvQxge9xRA/nCPYR0LDJ4l6oLHiTjT5cuXW2NBiByenXA93LfUj8YsDBDk/kgbA/liF2MvZVFukdwy9zqZMGwLKRSzcsfzt8hB0w6TfYe9RWr4MVHHBkd341FuRlRarBteLsvk1uk3yDMtj0tGquRzO/2f8EN4TIMKPUJF4gtUeq2NkK04HI5+jEhViOQcT026xJgGfqwyCq369QNL5MllKtHZFXLKnuNkvzGRco1o83/0C/7MzujjI9cHmFKT+g7Mu6Mpn8gYsdTeXvK5kpz/SIfMbs/JcdvUyIzlCbnrlaz86phBktFnXkjWRe/CvEMbvrHl2yBhDMYrw5jeX//61/LXv/7VdAP0nttuu810EvQhlP59991X9t9/fyMHDz/8sJGX22+/3cpDB0GnIQIG4gOhwatD6BheEyJW8PRgbCXsn6gZDMMkQt/w7OBVwrPDNdFLqB86CV4YxkzjfWLMDnWGJKHfQEwIafv73/9uuhh50Xcw8KJT4a2h3oCyMCpDxAiFQ0/CSM2S8D30OnSvhx56yDxG3CfjtNHrgm6EruTofejz9jE7aws+/Pnz59ugOT56PuAxY8bY+BVctBAcCAuCiBUBlygChgUC0kMeBBNXKx89nhpcqIzj2XPPPY0osA2RYZwMblpIBMSE8DSuDwFihhPqwWxruGYJl3vHO95hVhLqQ0NCoiyW73znO618yqXRgawwtog60OBAWBBMrollgsaHEDkala233tpiWLfZZhtrjBBiBBWyx/kPPvigHX/LW95isbdYYmhYgiCHZW8jlyhISS/1XPPT8tTyR2WfkfvJY3Mfla5kl+wzZn8ZlRqjlSlndvQKusMDk9rpaYdaVaq2HxOds3y2rEi3yvaNO0l9VYN2t9ZlazZ+7A7fjq5zqr8fh6N/w9pzlOWSFHVd6YtuqhwriWFcztXPt8iSQkqmNCTk0Cn1UluNNx1px/+geShCz/Ff8F8/GNXUBxo1lxFp4fkaiVFlvUWf/bNzl8vQuoxsOW6ozFiyQkY3pmVkfRUnal4tgZBDK23DAnKC4g6hINoEPQjjLEQEQAZQ9DHoohegRxCaxjrnQGrQP4h+QUdCr8FrwgQFTDaA54XyCJsn4gUyQ3kYev/zn/+Y/kXIG3oVhmXGzHBNroNRGMLEeUTHXHDBBUZCKIO6hv3oMxAXwuDe+ta3ygknnGA6DfUjQgZiBBFiDNCJJ55ox9Gp0MXQsfDwoBdh6CZqB32M5wBR+uQnP2kRPWHoAWC5sXSkzR2M2XGysxYIXhC8GwgjAktoGFYDBqZtv/32Rhpg8rhAIRRYHSA7HIfQ4PLkw4a4QGIgLWxjUYDQIEgIO0QKEoKAQSBw7UI+8ORAUrgO+TiOO5g6YfVA2CFZzFJC+SyJVUXYsCrQUCCIEBjqw8xxWGAgKpAXGhSE9iMf+YgRNQgOXiW8VdwT9SBx/9SdhoX7hgQh6Ah9nOiAjSXIxWJBnmh+VO6Yc5OMrBot+VReHl56rxw4+lDZbdDe1i14o9Jb0KfLDHf6h4uGrpjf3oH8DKkZIhMbt5Bnlz4pc9tmy6iG0dKYHqw5OK7JjFrROfxzOBz9HCrjKNz4bPgrqPLMuJw5K0pyzSs5aUqV5PgdhshWg0qSMY+P5kcJpm1AzBlv4mRnvRCRRU3l5pIE0SxKGheBwGnmtqfkmQWdsuPIKtl9TK386ZE2GTOoSkbXld9YuY3e0Aj9K0t0FfQJ9A7IAVElGErRRwB6BfrTd77zHdMz0H/QKRj3i3EWzwkkBv0JTw0EBoMuJAYjMwZmyAceGWZbmzlzpo3/QT9iymd0FiYH4DzIDsQJYzI6FnWgrPe///0WUocBGt2IyZ1OPfVUuzb6FfeBPhVmWWM/ZUKKGFMEyBMSOh9GaEgWdcAwjZeIEDzu7bzzzjNdD92L/MGjw7qj9wHZcR/aWiB8kCxR6FH6Q2wo4MMNKRCjSnAuVgk8LlgLEGSEgW1CxgDeHKwMCDEWAAQeMoPgsB5C4MIU1xAeXK8QDuqEkDNJAl4Z1klYG3APUy/ycx51hxAhoJCn+P3Flwg9As99YfXAGgKhg9zgzoUEIdiE8pGP8vsCK/Kt8vKyZ6RUKMnUQdvKzBWvSF2qSibVT9SjTHfaN/XaPFB+ttqSRBMQaOOvidkHUom0jK2dIFOatpSFxXkyo/kVydvgWhSgqOuOQjIcDkd/B8QFcY8C07Q/0SVSjAQv6sgh+jK6qiSj63UlkbUDGDWiPPwPor7Fse7gSUJtaD+1k7Zkz1ZX8Zc3VCVldGNScoW8zG/plDENGWnLJ+WJeW3SXtR3xvuwknoP6A4hASJSiHiBUBBBgvGVgfzoPIS14bEJegn6CNEq6BboHBAhyA5GX4gOeQifh7wQ4sZ+dCPG8gSPSZjZNlwfoOswpua3v/2tXRsShmEXYkWYHcMRzjjjDCMmnEt90JcoG/0GfQvdCwT9jjwYi/EOYaCG0DCeB8IDmeO+mQQB7xVRNRAtCF78fMfGhZOdtQTCQ0IYEF7AB42wsg9AIoLXhbxsIwhYOYj9JEQMgUZ4ICIIHfkQDkgUecO0ipRz4YUXyl/+8hcbl/OrX/3KLAs0FggW6wF4bLA84HFito944hj1CcLF9SBTWDK4XpguOtwfCXLEXPYM+OPesKQQEkcDQXnUh4aAYzQYNEo0KCB+rY2FOZ0zZVbbTBlaNVwm1k+WpZ2LZHB6uAyvH22Nu3/kvQd92+W1inV98Nh/k9rJ7jhiZ+kstcmM1lekOdvcnQtu1Nudr8Ph2FBAwstSrv+xpG3NqozPaYkGwk8enJKmDCp5gPYp0RkG+hfHGwB9K30sq/ZsI7Bek0zIOCU46XRSZjarjqKKtWoV8tzSgsxpxaMW5dsY4D2jH+HJwKCLznDVVVeZTnT88cd3j9shT8hLKBshZniB2IcuhH7FdtCz8N5g0OU4uhA6CbPdAo5DhjAqA/QcyMWPfvQjGzsNwYLQoGsB9BYIGFEx6DWQEsolocOg/2CA5hocA+wPdWY6bcgYOh3GaCZsYhZd9C7IGToSOh5gjDeEivMcfQPXA9cC4eNnoBrChiuVfbhoGYsDMUEYCev63ve+Z3mDUCAkhIUxDSIeEIgEwsk5CB2Cj/WAgW3bbrutbUN2sEQww8h3v/tds2AwYI7BexAPPEPEqwbg3cGKADG66KKLVkkcqxQw3McIPzOq4XIG1DV4qwhVI5YVYaUuTFRAo4H7FoGlsWFgHvfINNqQP+oUrrOxBfrm6ddqQ1ct+447WEY0DZdce5fsPmofaUoOteNJNG9Hr4AJCeh6E3mlNkw7ncxLLp2VZIEQlqQUUgWZWrutZDpq5cX25+XBpXdJu/5FChD/p5QYRbMYOhyO/gyUa6YXwZiXVOVBl4VOmdNWkHtfbZdRdSK7T66VppqEZJL1KvsJySVLFuaWYgpqK8ND2NYXReOM0MiC/U/bmyxlbQICpnzI6LOeMjQl44Y2yDNLS/JcS0nes+tQWbq8Ta56brm80BoRpY0BiAfRHugL6A/oNoSDEbnC7xISTg8BQOdA/4GYMNPru9/9bvO2EF4PQYJQ8FMfkKADDzzQ9BQiTL761a/a7LOMxyHaJBAVPDuM9UFHCwZZ8mEsphzy4Bn69re/bWTmox/9qP08CLoV+hZ6GLoOYW5MgkC4HAQmlA0YmgBBImoGkoOOxWQIkC/IFNE3eJ44hxA+xvbwMyBMNBUM5Y6NDyc7awkUe8bbQFCCAOL9wJJAOBf7IT9YERAySBEfO8KGpQGBpox3vetdRjSwGOAaJQ8WAdYhJ4yZwY2LEEJyIEUkykD4GLzHdIgIYwANAJ4VrovgxROCSx0CsKaQPvWpT5kgAurFtSBSuHkZX0T9qRMNABYX6sM0j/yIKvVDoHkGHEPIcedSD8oKrtoNAcozO5a10yvXu7dLRWntapUJg8bJmEFjZGlns9Sk62VM7Wj6BClpD5G3Exy9AXsf0Ur0TrQDZrrphH4CeG4KiZyqN1UytGaEdGnHPLv1VVnetszyReeW36nD4ejXiKRUKYu2ubS9KN4FXZ+1tCgtuYQMb0pKY70qFQh/KSF5fkTUQluL1ha4mL8xRI+Pvpx3QOLZ0slBJKM+t75atB+slmwuL7NaizJNyc/Wo5tk+pIOeX5ph+WNWlzOLReh59nrfCOpAij7ySSTISRsTA7jYzCQQjrQcfB8QFDIx1iZH//ox6ZTsA8PDDoIxtWqTJXpJsy2xs92QBYYo0yZEB7y8y2iR6F/4A36+te/Ltddd71F0oQfCUU/Y0jAsccca79JyGxsGJ3ZTxnvefd75IvnflF23GFHufuuu2Xo0GE2ey6kLMCM0ccdL1/+8ldsZttRI0fZZAaErnV2dFqUCxNSnavl8NuEU6dMtfKJ5KH+kDt0uchkEP31+CxDWgWve9CxFvCpp9cAFHceEZYHPB6Mh+GDRUAQSLwceFUYsM9+PDi4bRFUQs0gRkxWQMwm3h+sG7B83LgMmiOEDUGlfKwKEBYITXDFYn3AVcqPmCI41AVyAeGg8SCkjZlGmLUEC0ec2ADiUffee29zxXI+81HQuCC4gPyUicAS0wppQjixRnBvWGIYo0M+ymIqa9y/TC1JvXk+IfQOV3AcHH+jgMzQqSaKae04ox8PTedwKZekkM5LW7ZZ/vz072W/rQ+QHep2lVmLZsodzdfL27c4UxozjVa/qoL2AJHn2tEH4Pu6cfqVcl/LnZJKp+So0SfJjsP2UBKUlDSx5EmYkVt8HY7+DBRkVGVmUkzyQ86porSrrv2vZzrlpul5OXWrLjl02iipc1HuE9BX4vO5d1ZeLn5isWw7bpCcs3O13DZL5Ponlsr44dXymTfV8gZpeSWhBLWY0qTdtHnp0ASty36D/baW09q6wnSYTFVaCnnCvvSaeq03DO1L2lZ0SEcnwwGGRlUt1xtVgcmKli5ttmvX1zN+Rw+slR6yUg1evqxFCVKTpKhvKB8YcRfV0dqkq7NTho8YVqHjlCSbLUhLc7Ppgo1NDdbfrSu6S1yl2hGZXQn3U6wL9D0lnOysAfHHU/mo2IYEQFQCyWAfiY99dSA/wIUbFxYsEyCEk3EskK04iWGbvFwjXC8cj5cHyBffxzr7wjUCKAOrCfu5JuWRwjoI9QPh/jgPhGuwHdYr67I+oPkmJEp7WN3SpB1tjsGvun9hdr5c++y1svv4PWWXoXtIe2mF3LbgOmlKDZY3Dz5EUqpAFzJ55TnMEueNQ1+hoN/E7M6X5KbZ18jcFXNkWGqknLPtZ8udCVZf3m85s8Ph6JeI/AG0w8ymqKKrbfBzK4ryhztnyfLUUPnM3vUybShzsDn6AgW6x1KXLFAG+venCjJ34VL5/nETVN9IKAHqkKueXy6f32+UjFY2mrauuUuJToa3qX+Rr912b4B+2/QAltFmucgNUC4l2n1GegbJ9hWj7XAP697fR+WW16ysVVDWc6LvP4Jdo7xfN6xOpg/pqdHZUf3WFYR/RyvRYiW4Vri+d5jrAn0PrgGuC/hw4ymQAAhCIAekQCQgCj2B4yTKiCOUE/YHgWafCVEZ7AvXYL2ynDjix8MynAvi5+L54VoQmVCPeH1C/SrPj5cRX99QKGH5L9GYYH+K7FJZ7WifWfy0zE++KpMGTRbdIa3ZFlmSXSwja0cZ0UliTdKER8jRlyjKoKoh2smOtfeyXJbaOB0+aTqn7vbb4XD0W9Cyd9ucrJlPyPwVIstzIulkXgZVa7/BbkefIOp5S9JYnZChtSnpyBWUeCakLlWUrYZnZNLgWnlufrtkdX+xoClRZX1jMREFeuOx0x5flW3t099goiT703Vt5F9zfH2TeRV1mdJ+Xfd0l83dc1XVrKL70BuqPPf1E19uuZwejtsxXdr17alGz2mVc9iLzmHXj46vT1o9Vl7Pse7wtmkDY3WK/7qQgjixCajM31NZPZX5esdAuBbHQwrbcfS0vzJPr4DqmX89WtrvNRQTMq99rrzU/IIUkllpTDUZIVqRb5G2zhXSlB6seTW/cjIGzUcbjr4CT78+0ShjaydKdaZG2qVN8hIN1KTLcjgcmw4wOGE+ouuYsbgg2VStzfrVUK1tcw99l2PjIOryklKdSsmIelW8qzOqeHMgL8N1e49RVfLIrFaZ256XIgZEPSOlyjVZcnoy4Wz2Uq2kdUtlf8prE6RE02v2r2eyr0v1juh6UbklSIKFQZfzlY+H1L1/DckIDGWaXhOllWWUrxWubaRk5Tndecr7La33fb8e1iaPoyfwNhxrCZT7kOII25XHK/MFBG/J6hIIy4D4MVB5fHXoKV9PZVWmsD/u2YkfD/tAfB1UHn8jsMbHrC40c9FA1xWJFnlm6SOytGORTGncVjKJKillStKSb5ZcPiv1ycbIGwQxshL8M+9L8AbShSoZlhkpDVWN2iMXZVl+sfUFZlHz1+NwbFJgbEhem/iZizu07a2STKlLakyBNnXU0QdADYfu8PtmI+vSUpVh3jw7YDO1bTe8WmZ2itwzK/rdnWSx0/rGZIlB8+jpBTMmFnRjXRNvftV9CUvsLyaj9VWPr19SDUCXlFsuW9chIKteP3b8NfVac6LM7vVyGZYqrrvKOfE8er9R3pXH1yUFYIjuyfDtWD+4mrEGBMV9dQp9T8fXdOz1EM8f1uPnrO542NcTVpevcjugp/1hX+WxsN7TsQ2CsqxnE1kzOpXyJbn4lT/L44sfkwPGHyanjT1LkvmUtGfbZHrLy9KshKcpMVib/LR0ibbsEJ54C+LoIyRkXM1E2aFpNxlSGiF3zb9Fcvp+eKcFDzN0OPo9gkJnYUQquI/PK8q81qykUkkZ35CSqkSwcDv6AtGzJ8QrL1sOT8q4xlp5dEGnJIr6bpTcDG8QOWbbQfLwwpyce/tyuXOe9quFPFq1pHOMjU1qm5yUVLG47qnUw77X27++KZTHsjJV5utp/7qmeDmVaXX54tvxPGuZCO228O4AVkNyrDec7Dj6N7T9LpaU6OhqR6lLZhdmyNLmxTKtaXvZbsiOkkmkhV/j7yx2GuGpS9db3KzSLiNeqzQajj6Cqkj6HpkBaFTVWCWjg2R+y2xpL7VHTjsOOhyOfg4C2LQ95V++IK8uWm7ymyx2yeCajLbTkZXd0YfA4KhKdn2mKMPrUzJrubaxkrKZyjh24MRa2Xcs7yor1z+/RFoKKenSQ13JlHRqv5nXtrioxMhT36XoF6k09SRLqDOu0qwXfDY2R79GoZi3MNhCsSCzWqfLfcvulmK2KAeNP0zG1o+3wYDEGk9vfUFumn6dVFWn5aypH5NEUhvuZE7SuOi1AWH8jqNvQMdqc39rh8u4qutm/ltebnlW3r7VmTK1cRq2xB7bdYfD0X+AzblQLEm6mNK1rPzh/oXyxPKU5NMiR0yuleO3ahR+W8Wb2r6BqXL6L1Hokpy+hGunl2T+wiVyxj7jpdpmKytIUd9Pc64ktz69QO6Zl5Ddx2Vkm5FpGVxbJXVVaanTN+uEtW9Rl05KOrVSjjDcvgb+itYJCbBZkx1+jytRlK5Euzy5+AlZ3LFASinGhfAlEXeJOcS5YF+iI98pS/LzZUHbPKmSGtmycRs5fuIpkinxi8maIanvL5uVB5feLXfOvVX2HLWfHDb+CD2Q5vUq0SlJCrKz+pnAHb2MHO58OlEVJcILn259RC6Z+RfZKr2TvHXa26Wx2BR7P0HezDdXXnc4HH2O8g80F1VpTqtMf/7WFdKSb5dR6S55+55TZYfGvAo4Uxk7+gQ0nZqYXU1bXXm5JSnnP7xCztlliGzdWJC8as/pUjSza0lJT4u+zyufXSozmwuyrKskWX4Pp5DXftXpal9ifH1OTttjgkyoZsxVTorIFMER+r4kmZCcKj4Z7xrXCU52sto2pErSnmyRy5+4ROYWZklXdbvN4JUupm2J0uXoO5S04c4oyRnTNFGmDNpSpjZsKaNSY/SIklFtARhQ2dHVJrfPu06ebnlKDhx3mOwzfF89UcmOvjpmBzKy4+13n4Hf2UlgOKCtLqVkfmmmnP/iT2VIxxh527R3yMSaSdaIAwuTUTjRcTj6GVTZwoDETIrYJj5+w3LpShZkq7pOOWXvLWRSWpXsZDoyQjk2PsqaXDTqIyfLCxn52i0L5V3bDZZ9xtIfahuczFg+1OhSUUlOLinLO/KypLMgLbmCZPWY2wX7FkNqE7Lt8Dpp0D6wpPJVTKCLmsZjOk1WBazW+8d1gpOdaPZbyaa75NXWl2V+x1wlPwVVkKO50vm8ulsQR5+gLlkrg2tGyOCqYVKfqrMfCBVtAHgr5ndTwW/rbJarZlwmi/OL5fAJx8sOTTvoAW3O9fXxeacssNyKc/QBMEgRQmFThOqLaJcWOe/5r0u6tVaOnXyi7Dx8N+U63sU6HP0a2pYiy4VEXqU4KR+6bql5C/YZnpeTdhsjw2iRYTrOdvoGdIq8I338hVJB31NSPn7dfDlx6yY5amqNzaAniSgiIlksSqLI5AT0oykpJDXp6danUpajz8B04dWqr2Ag5H2gvKTspRRsBsS8vsAaV2jWCZs92SnSIOgfDTefVRqbhlJna6r1g2IqRm+4+xZdykhxykTBEfpO7F3ZhNRRq6ytweMdD8qNr14ho+rHy9ET3iYj0iP0GK2FHtYGI5ojyJXpvkLJ3O9ln43+x+8kffOpz0miTmRc+yQ5YaeTZXhijBHT7h9VY1FejX7Vw8PaHI6+RKQpmMosi3NJ+eJtLZLUPvLd21TJ/hOqdS89qcpo0hWxvkA0eQTvJ6lkJ2mhhh+9Yb5MGpKW9+4xXIZnopbUfqtOl6kSwcWcF1pX9rPH319fIlHqUr1FyWcibf0hXjgiVMKb4i0lypEQjrUDXGez/qoJqWHsR6oEzSkrw1BotGt0ZWJX+aY89VmyX0S2F8KO6Ae8+CE028YtnyrI8q4lki1mZUj1UKlO1OiRslpM2+Doe3S/h6jBhuwMygyVfCEnLcVmWZpbqnv9ZTkc/Ro0qqp0YZRo7kSSS1Kv/eWwumo9hOc2yuboK/BGUIVLFhXMO0mX8rKssyDLCNnXfjOaNjzyFCTw0GlKaT+aUAJEt1rQvhb7rqe+S6VkWt9gOnpX9j6jcP2SvtRo8giSY12xWZMdJifA8s8y+oCiRKNNg85f9Ig89VXKFNNGRhH+qBnnnaAw65tSsprQY8u6luK3lyGZYVKTqrWGwbIpvFnoH0DCgL0PfTejqkdLqaso2VSXLGhdoLt4oRwKcudwOPojkM6l7QQ9FWRwOi+D67QdZi+2U1PGHH0Few9AF/SDg6oS0llIyJJ2Ji3Q40p0ksWkLelPeYeMwoIYET6VttP5z1OfJdVrIlLK+2IPeipvikmzIDyazbHOQKPcbGEfjVk0SBHpIR65kMxLkXEhus3H5qnvUkRIozhkUnhPzAgU/po7l5tHZ3B6qFKiDC/V3i8Le8XRlqMPEQiM+dy01RlbO16S+aRkk12yZMUiyTPFOHn8hTkc/Rdl+VzWltVFXgYlumRQLQei3zZz4e172FvQ/0jjBzdIZ7Yoi/V9EU2MzhMlVL+UrjBhQVqTBSAaCBX31HeJN2jvwlyl6Kb8D42NggyjWYId64rNm+yUVHHWDyqydiibLqQkxdKYNV4DHo99Xp76KmmLzZ9FF6rU2wx55RYbMkSDMG/pHBnVOEZG1Y62vOyOWnuO6382q56jr5DQd8HbjNrupL6Okuw8ancZnBgsnYk2md86X+Ytmqd5IgODvTeHw9Ev0ZUXmb20TfvKrGwzqlaqVb4ZI8Jcbdb2OvoEZiBUlY5xHqa5KKHZaVKj5HJFmbGkS1o7+Z2dnDbBWW1nI+MSPzgaEVWg20lGxHrqyxQZdHkXIoVkQV+L6qWFpGRU7jLFoupB/G6dY10xoMiOhZ7F0prAL+2T9AuLEqvsiz8WU5o3XDJ9j4v1sD9aRqnyePxYlKJysNZU5omWq5YXUthXeV6/TdqB0gCEmWIAs8zQIHCYMT3tpTapra6XunRD1OBrYw/HMe3aVkiOvgITFPBecM0XEtrR6ttsSDbJ4PohktBGvFmWyWyZrg16mcjqi8bDyrKIQaJcjsPh6DtE7XBClnZpm5tVpauYllGD6yRNGJQ2xqv0m44+QGgptQ3V1YIqyWMyIsOrGNdakqU5MxvqW0rbuzIzYugey/0tf+UdGyxFqhjLKIX9hQJ62mv3h7yq1+tSN3U7Wmd/tF2Z4vtDeeGceD7Smspa28T5lWWEa7Of68SPrW2yd1De5F3ZHkQLXmrvqEpXHOuKAd06rYn8mBWkLPT8I6Fc5QtRfGuE8oENkAoFPEkIAVLw2uOrVnGlMBUjZhLtVkT3Em3TybBJ2VG+lQIYLVdFVB5EYWX5UVn9NNlCK6nL7tuJHSalM2lprBokVSltBLobN2tpdE3X2XT0MazJ1mX0LiGpwxpHmDc1J1lpLTXrN1mWRcsdwFo41+Fw9Bm0s+CvpTMnHV056zmHDop+8cNkV1dcSvsQ+vDp/jBmRu8hIQ3V+o4aaqS1Q9vYLqgqR1D7oraWrfD/G0lxXSIs0UfQS1YeD3pYdE4yNmsf+8kfzrX/+aDK50brYGW57CeFa4R9AfFz4im+P5RRmSfsJ3G9ULeeUvzYSoTrrHt6zR/ldB9m3Y0K64MB89R6IjMBKPevdzyOfD5vKSIkGw5cH+EuFJi15rV1WSmAEcgT8nEsfk7lNgj54/tZD/ceP8b9xbf7NSyeGJMGE2rqO9HHlFRCisWDjTbplMHJYbJlwzSbWU8z2x8/oMYTtS2Pce1bpJnWnaYG0wITTeh3p73yzkP2kkGJodJZape5S2Yr6emybzKafppG3f5ZcjgcfQwV23yhJDNbVsiirk4ZP7RextWodKrMMnC6qH+bQI8ygEEoYfT7coAesqE6KVNHNMmKjry8sDxrfWdvIOgvQadAzyGh87Av6ByAJceWL19u2wA9JegqQfdinTxdXVG/EBDyUkbIm8vlVtGL2G5ubrZlJcizdOnSHo8FhPqHa4TrxROo1NsA5VPnlpaW8h5Hf8CAo4jhYw8fI8hms91CsSYsWLBAXnrpJWlvby/v2TCgXtQBAWhtbS3vXYlQbxAX2rgw0WBUCllYUl/KDtucjzB3dnbaNgjlLly4sLs+8ev2b1DPKHGH8BeU5kXtC6QpOUiGZIavvHfz6pDXLSD9Abyn6M0A/QZZ6Csakh4uQ6qHmTe1Pd+uBFW/7XJGLFoOh6M/ISHZUlKacyXJqhI7alCNZFSY6UKsxdUVk21Hn6DcM0YbCnq/VLIkwxvSkkllZEHbSp1oQyOuR7COLkJCL0HPgLQE8sFxSNDf//5302nQz8i7bNkyWwLOIe/FF18sc+fONb2H81iSh/JInEOibLbtG9T06quvyj//+U9ZvHixlRcHdbrgggtkxowZtk3+SlSW31MKJCzoVSFRR3TIq6++ulyaoz8g9X+K8vqAQCAE999/v0ycONE+yFtvvdUEZ9SoUeVcKxE+9PDB/uxnP5OrrrpKJkyYIOPGjetWoEHI8/zzz1siD0LZ0dEhjz32mBGLpqamcu4ofwDnIeA33nij5d11113LR1Yi1IUyEZZUKiXV1dVWDvvuuecemTdvnowcOdKOBTcw5z300ENy7733yi677GL7eA5PP/20rFixQoYPX0kEWP7rX/+SnXfe2Y7NmTPH0vz5840EkRobGyWdLv/uUBnc75AhQ0zIH3zwQXu21AmEegeE5xS//zcCSrExOqwzao8VbbdRjl9Y+pzkC1nZbtiOkk5U2bEwyD36fR5O4h8nOfoCBTxxvDeFfctE/pcnmpjd/qrM65wtmWJGdh+7l1SVou/d3pkuLfm7czj6Htqmt+REHl3QIfM6irLL2EaZ1ojlvijFJGNBaPMJj3L0KWg7rUvW/7Qv7NC+8ul5HZLTnQdPrKNhtWy9Afp9dK6//e1vppNAQtAbIC0vvPCCrUNu0Md+//vfywknnCAzZ86Uf//736ZXoItMmzbNdDjIxo9//GPZaqutTNdC52EfeR944AHTo5588snuNH36dNNLamtr5cUXX5QbbrhBdtttN9tGH+KaJMr4zW9+IzvssIOMGTPG6stxEjoVfc4f//hHeeSRR+Txxx/vTk888YRdM2wPHTrUdErI01133WXHn3vuOXn22WflvvvuM32NstgX0vjx46WqauWYG+vrHL2ObygS+nGuqqluouA2gjXgi1/8on34e+21l328zzzzjAkKQgPYx/rb3vY22+ZcPlgElPUtt9xSLrvsMvuYv/e975kQZDIZW/JRI4BvfetbTZDq6urklVdeMWE+/PDDZcqUKZYXIYBskJ/rUTfKRrAQxJ122sn2BeH68Ic/bOfMmjXL6kLeX//61/KBD3zAjpP+/Oc/y0knnSTDhg2Tmpoaazj+9Kc/mUuWsiBCkC3ycuzll1+WSZMm2bHdd99d3vKWtxgh+8c//iHvf//7TfjuvPNOa3B4Ptwfni3K33777bvrRkNCvbfbbjv5y1/+Yo0Y9eJZcxxwDvceyBkIyzcE/Tr5QIuJnM3GViqHtKEsN6eWy7+e+5vsPnxv2XHYbpoxYRNOMHW4DZbV7XKrr+1/pGw7Nj4KJX6qTt8bn4O+jiIDmvX9FYoFebr9Mbnp1aulvdguZ23/URmbnGDfHXmN4NosTwpeJUuHw9E3UEF8eVlBLnxymczsFPnCvoNkm7q0yWmJvsIk1clOX4GIBlUb9PmHdxDNjrdM39U/n22VJxd1yI8PGyNVvdQVorMAjKgPP/yw6Qe33Xab6TYQnGuvvdZ0BEjB2LFj5Y477pDzzz/f8l533XWmN7H/Pe95j22j7/zoRz8yDxA60Yc+9CGZOnWqESG2OY4egw4G2M81DjjgADPOct4nPvEJMxxjvA3149zf/e53pvdsvfXWdh7H0KkgQBh7qW/IH/QY9Cj0pLCffoptyobI4cmxvkuBNwr9i7qgV3Fv6GTvfOc7bZ0yKWeD6EiONUKfc2JAeXb4GLEWQFT4qA466CATDpR6PuJDDjnESA5kho8cIeFjI6zs+9//vlxzzTXy5S9/WbbYYgvznmAZQMEfPXq0ld/W1ibf/va37YPGA/Loo48a+4cIIFyQDpa33HKLlQ3BwKvCNRHybbfdVrbZZhvZZ599ZPLkybZOXUhsB8LFdWkAQkgdVgy2cc1C4iAb7D/iiCPM+7Tjjjsa8TrwwAPN6vHe975X9t9/fzn44IONVOFFwloC+aJ8yB8WF4QNTxOWCO7lf//7n5VNeZAkGgGeDw0D5I7rX3nllWYZwcKBReapp56y50vjwD1iRQkCHJZvDDQs2jBohxp5alB+cdgnZXFhkTy+9AEjOoOqBltuSI4pycVIYeY3eqLG3xuVvgNPX98ar0C/CX6t216Opk4lOdOXvCRtyVbZYfBO9sOwWIeBvUd7d3aaw+HoQxAENbc1K08syEpzPiNHblElgzK0s6vKtItqXyEK38aLzm/SsU0LStu7oL0kLyxql0OmNvUa2QlAFyBSBKDwY3QGGHkHDx5sxxoaGiyM7JhjjjFvDnoN+hUGYwy+F154oRl2IQvoLuSFAB166KFGFsgDscF4S7noQ3h/MDzj3VmyZIkZadG1ICS333676S0YhEmcA7nhmhATwt04H92P8gOJIbEd1uOJPCT0QcpC/xs0aJDdG7oV4XZ77723GaDRAzFmoyOhF21YHcmxJgwozw7sGSsA7kU+Pm4LlyEECGU+uBw5BnM/7rjjLJQLpR0PCoLwmc98xj5OENyo7373u+Vd73qXWQHYhweHc/m4UfSxTPCBn3jiibLnnnta+V/96leNZOD94BwE4gtf+IKccsopRkoAblQAKeN8zuMeFi1aZKSH86644go7BzKFwEG0yM99QaZGjBhh5AaSUl9fb+Xdfffddl9scw4ND/d76qmnGjFCIC+55BKzklAuDQ3WFKww1IHGg2fF+QgijcfnPvc5u28sJTzfs88+2yw21C14crhWOGeDCrK+R+hK5NlJSZFwqCK/+JySZ9ufkv/MuFDO2f5z0pQYpHvS2tBrnqSStILmI2sCr8KqIXmOjYuoiSkoeaGXhbxop6y9cU5lc3Furtw6/Tp5If+svH3iu2X7pp273xe/McA7N3if4HD0KXIqxg/NaZErns3K7I6M/OLIBhmaKXvaEyjWhLIBF9a+QIk2VtvUZCmjbSctLb+lk5RCKScPzC/JxY8skf87ZJyMsB+B3fAIqiSenWAExntzzjnnrOLZgYSgw6BDoHsRvoaBGD0J/Qj7O/kgOpAjysE4i/cETw6h+himMdxijIawYAz+5S9/aQbYfffd14zO6Cx4dtCrggGadXQcvDAYhNGJqDfXRmcjQYQIQ2M/OhHEhvMAeg71YT/Hyc+9UTdAiBplcX0MyMcff7ydg35Ffgzg1J/1uK7k6F3ocx44c9jxgeHJ+OlPf2ofMIJy1llnWcIywIcN+WD79NNPNwb/85//3EgIggQYtIYiT0JA8fJAkPAUffSjHzX3KwIDGYBo4MVgvA4hX29605vMTUniQyZBtBAEzuOjDmF01JX64WH54Q9/aFYKjiMUEA88PcG7REwpXh+En2sTLobXhXskP4KDdQQvz3777SdvfvOb5bTTTrOQNawgRx11lK1TFqSHcyEokCoamt/+9rf2HLBGfO1rX5PvfOc78t3vfrfbW4MnB0sIpIexTwgvXjKEPwg+jQFCzj2QuPcNBi0KukOHClY2DSVZsnyR5BJdUpOo1WY9ckV3XztWheh8R5/CGvXy2ythbdQ3mixKdbpGhjUMM2K6oqPVpn3vfl+6YI1tf4cOR+8iSJlJGu1ouT0NMpjX9Zb2TlPc2MmPieI5x3sQNbv2n6OPEb3H6L2BlPaOQ2ozMrixXlZ08jtn0bHo3eqavWdblP9bd4R+F50HskO0DCQEYoF+hZcDXQF9Cd2BxDmQBhJ6A/vwgnzjG9+Qk08+2bwzl156qXl9yIsOhu6BgZbhAeT51re+ZfocOhWRM1wDUF4AegrG6MMOO0yOPvpo04cwzEI8MFyzn4TRmTpj5MaQTSTMzTffbEMFGAMOcfvJT35iZA2djuPoRtQf4zTeISJliC5CRiibfRijeSbkATwjEJ6ZY+NgwHh2QPBOfPaznzWLAOFbfGA33XSTWRIQlCBgkBU8IAgFnhSEkmNxIQEICgKIMo8A4/2BjJCPwfqQgC996Uvyhz/8QfbYYw8TQISSEDqECTJBfkLAIEUQKer0yU9+0sgZ5zApwnnnnWchZP/9739NcBF8PFJYDrgv6gHZwPIBoYKIEAZHHupGHiwS3CfEBYR74b4gOJSFZ4dYVywiNAzUjTJoNCCDkDDIF40Dgss18BZhNeEZBQ/Spz/9aQub47pcn2eNGxiEZ1z5LNcL2i6UElmjOimpskaanUsL8+XqF66QVwvT5cs7fsca7bT+WdiTKtMGXZSbddvv6D/gGwny9lzLU/LvORfLhNJkOXzKUTKiZowkixkjQykLydBOQvP5jxY6HL0H8wxoK0uLmSphyY5a1YLKXkrb3MXZolzx9FJ5dE6XFFNV8osjhkomSSMbeWJLKqdR0KnLaV9gpSKn9NPeH/70jCR1fVkhIze9uEyGVCVl/8kNUst7038FTWk7Mbwz2tqyN30dENpzFHkIAJ4ddBQG6RMdg56AJwd9ApKAngJ5QD/CK3P99debToIOhA6FvoRRGe8Mww9Yp3zyEOHCPggEOg3GWsLsOY/JpdC94p4dDMahjhAZdC30KerKmGz0P8gTBmYIUzDcooPhjeIY+s7s2bPNOE5IXCXQqyBCDHkgLA6ChnEaIsYxdEj0JQzkcWwQHcmxRuhzHjienQA+YD4yFPMwuxgCgoeGdcbBsERQyAeTJ6zrr3/9q7lFKxMkBhclggIgUZSFZ4UlQOAIc0MoENxATvDC4GU544wzjDzgSsUigJWDY7hbiS8lTAxAcgiPIyEEWBooh3pCVjgO2Mc218dbRMMBEcOKQF0QWsYqsSThGWKJtwbiwnXxcBHPiicJAUc4Q30ghTQuxx57rBx55JF2PcgLjUAAJAlvEnmwllCHILjkDc9rw6A8csOK1P9otLLLpLmrWeoTjXqEzjgV5QpEx9FvEb6N8L3UZmqlMd0kzfllki1mo/FWSQhqdJylv1WHo3fB2I6VcoZqsFLuONaVE2nNRqHEVaosoy8HDZtVl9F+BFS7oN7psi5VlBH1KZm1vEtW5JTQFKLfmLEcq7y48jnrAdrzoLegJ6FDoLsQVQIJQOFHbyEShHz0A6EPYBnGLRPxgs5FQj9jvA6GXAgMESnoNkSYQB5+9atfmV7EEIJQTmX/gvEXHQbjNEMDmJjqYx/7mOmBEBf0IsZFQ26CrgMgaxAVzqfeleA66JvhPhgHzngk1qnbmWeeacZhSBLG4v/85z/lMx19gfX/svshGKTGuBI+fgQMgeNDxI1KCFcgEny4EBKAW5UPHvKBko/iH094WvB0AD5s8rzjHe+wMTBYEIJgQRQIG4MQICQsqQNCiCeGsUCEujFWh9nQcJviXQJYHmgA8PJ85CMfMe8PAokblHX2ffCDHzSChQXjfe97n3mPyE8IG+cjlAgWAgzpoVGA2CF8wapASBszo4SxNZCu4F5mEgL286x4JpyPJ4q6x8F5JCw3WE7wEjFDGySO5xNAng2BiLvwHxMTRH0r0eFLOhZJR6lNRteP0aPY/JXskLnc+To2HdRm6mVQZqi0JVqlNdcsJX6RWl9lULVYOol1ODYGoga0ZO13ZFwzJUF3d+aK0pJNSCGRklo9RI4ohZY57HH0FfDFRW+At4aJMGo7M6W8jKjLyKyWvLax5LKQCT3KevT2QJzurguCHgTQJyAM6APoARAYEIgB+lFeiUVcRyAPHh/2YWDFeIoBGWLDNkZcxgijk0Ai0OcgF3hq0KWIKuFc9Lt4VEnQ/8L4IKJViLjB+MtYbIzcDF9gBjgifYKhlrpiQGaCBSYX4HqVQN+EgHEvEBqM2ehe1AGSxrgi9CLIEvohdYjrSI6NiwFFdhiPAkkgjA1BwYtB3CcCgVsUAoJFAC8L4VoBfNwIDMSB4/GE2zH+geIBIQYT9ywD0AIgChAgZh5BSCAYCA7EC8GDHGBBQAgQIM6FRCEocXAt6nzRRRd1h90FUE58G+HFQwOpYTY5hJZtBJn6IcxsE6OKwNGAcIwy8OBQX8YyIbQ0NoSzIazvfe97bewPBIy88WuGbdzREC+IH67a+FTVGxLaHuuN02hHnyqzzCzPL5GXmp/XeuRlzzF72+wz3a21o9+DbyT+nQzODJEtqreUZbJYXl36iuSLee2KC9pJlzNEH0G07nA4ehEMaQfa15iMasvL7+go8VnWVpD5K6L1MXUo0QgoeViSONPltC8Rnj6kJbzJor4nxu1MHJKShV0peXx+VnKJKinkg15DPtaNAq0X0AnQXTAio9+gb+BJQeci4gUPD7oQ6VOf+pSRi6DPhP4A4/HXv/51GzcMYYDAoFNQFnoYPylCOezHGIvOw2RQlIWuQsKgi0eJ8xguQPmEyqEbnnvuuaYXMiECoXAYnQlPI/yNcDaGE+BN4jyMxIwd4n6YFAoDOWWBUF/GMxN+R37IGDog4fwMdUCXBITbEZpHpBHX5/4dfYNIGgYIwrTHjNH5yle+Yl4RPkLcqnzQTDQAEWKwGd4LgFAgJLgYIRgw/XgKVooAmDqD5iAWxJxyDAKDYCMMfMwIPUIJgWCgG3kZE4OVAgFFaBnkRv1Yv/zyy+061B3yQ/05jkUhhI5xnUCcgtBxDbw+jONBgCFh3BvXhODhlWIf9eQHR6kP5VA/BJSQO2awox48A8LpIE7kJ8wvXCcuoEHQuTbPm4YIIaee4VhIGwbl5heF17TfoiztWCzLViyVYQ0jZWh6hDbr0Z8hXHaVy2+oujg2JMJ3wlirwVVD9CNPSHO2WXLCINPo2zP463M4NgJCKxpXeaP1bKEoLV0Flc3IoDW4hr4I9472jZykycW0v2DVN2F9sTantfouU8mizGvulA59rQnVBejig28nWq4f0CuCnoTugg5D5AdRJ6yjI6FzkQfDL2Fp6CHoDegZ6BN4avC8kBdDM+WgFxFaRmQMES2QBojIL37xCyMRGJfRXYKOQoQLhmR0G4zO7CcKhigdrsN4Isb4UA4khgmeiMiBaOEBQu/heTEOG52OiaogTyDol5RPBA3hdUTboGtRJnoYYf14eTBkc31C89D58GahX3E/jr7BgPmdHT4myAk/+MmkAUytzMeHlYHpCBEKCA9eE0KvIAKwfD5UpiGEZPBx8hFjNQiJspjljDEqfKgIT7AGMEMaIXCUzQfNOp4fvCN4OyAYP/jBD2zAGmN/YPl4fBAYhIL6Uf6//vUvEzzKJwwPMsWgPjw7kJJAUKgnLljC4xBwzofIMXEBLlQ8M7iCuQ+IUoh9ZYnwIciQIawU7GNMUviRUkgRXho8XlggeE40EBAZ3LGMywl1odHAc0QYHfdCY2QNai+gWOK3frRlxnvDJTS91PK0vLT4OZk8ZCuZ1rSjVCVWjiUyxKqyChFy9EsQZtFV7JTHW+6XVFdapo6cJg2pRlWros6Tgc+gt74xh8MBrYlaykjKyv+XIrLTki/Jswva5PkWxkcWZJeRGZk2vCayQVmOgFW3HBsP2AJ5gxaKZq8hIi8QGn4HCU/Powuzsry1Q6aObpQR1fSpZOQ37Ip2nO2o1V13oBegw0BGiJ5BZ2C8NDoYHhDab0gFETfMcEY0DfoM+hGRN4TaM/QA3Qc9BQMxOhMhYOgY6FvoQRit0XOYLZexQFyXstHhwiQChJfxmz2MS0bfQW9BdyMcDeMuoXHodOhRnE89mDCKMczoNuhL6G6QtdDvQHrQrag7eYiUgZShX0LMmAyBeqODsmQIA0MXIHTcN+czxjqQQuB92sbBgPqdHW4jfPQIBAiKOSl8YBwjT/wjQ4kP51Q+jrgizzHyxT0dcXAct2ewVnBeOIfrh3LCdjjG/rgAxEEeEMoKZcRBGfF8YRknJ2zHjwGOh/3kCXVY3XVWh3XJu67IFbOS0mol8hkppPPaoCflgmd+JZ2ldjlu6ikyvmayJLuvH94dTX7v1cmxgaGit7SwWM5//jzJryjI4dOOlX0GH6gHCF9kfqCcfmPRuCyHw9E7wKSQsn6ERF+gS2b1UiF8tTUvVz4yTx7taJKGRFHO3LlBdhtdazO1qbpoeaNxdZq86e0b8LrCqxN+i64o+VLGWs0i70b3Xz+7TW58YrHsPHKwnLFbk5SS+v5K+OtK+i5V19G/SAtYdwQdBLyeDrG6Y+wLOktAKHNtdQzOD/pZuA7LuL5VqWutrj7x/aGcOOLbXDcQp3AtEJarK7+yLo7egT7/MF1H/4J+kpb0a2DDEpHChfIf668HPvbwEfGRxT8ojoUPN3yA7IOgkLACxFPIE8oJHzSo/JBZUkZYD0vOCdsgXjeOxclTKDOAPPGyKsE+zqecUFa4R4haOBb2xUE9wn6WAWz3dG8Bq1vvDVALLI6A//OSlWX5pTKyaZQ0JQcpCWIvuVZ9bo5NC9XJakkXqiSfycn89nn6NqN3SkugkhplcjgcvYZoDM5KyYP+FFVFQP6yqiw35/jRZpH6TEJq0xgiOBLOcRntF+h+DegYyWjGPAXdNKtThtVIY21GZi5ZKsvbu2w8FgSH95dQ0pMo8jMPQQNbt9T9x4U0sbT9YRmOaaVYdqfyH3kSKf3eYvvsBsi/ck+0jOWxv3JZyTRTp0fb4TosQz0qy+/Op3+hjiFv/LphX7QV3Y890HJKZaD8UX1DOWE7fv34tcP+yiSlgl5A5Q8RXLngiOpl5Q3HOqNfkp0IvPRoYWnliiF+yPaqNBODyjJs95TieeP5QjmVqafj4Tprcz3S6x0PZYbtUObapnB+ZerpGPvi5cefQVjGj8X3x49Xrvdmsi5VV+xyxaS0l9qU8ORlYv0UqU80RPstVzzpTscmhYz+pQsZKVYXZUHbXH332uwnohTZZPydOhy9CaQMTaqEvBG+ZhMT0A+IdBZT0lqqU+W4JE1VCanJRDKZNs2LfC6ffQ76QpKt8n6UnOoaBknTuXXPxOqUbDW8UeZ3FOWZxVnbl0+klNSmojA4Ot2gXa9rCtp8WNelefvCMhyrTD0dq9wXtk0xKO/v3lfejueNb/eUKs/T9VDHUOfV5aMO3fcTPx6WPZz3umVWJBZ4WVkaKSqvBaxcc6wL+Nb7KfRj0H8hEb6ULKU0qfjyOxyOzQKELmkzLIUk1o6EtHS1yPCqkTK2dgtJpdNSSq06m51jE4TKd1I726pUlSRSCWlua5auYpc28VGzDnnlz+Fw9CZiapRpvmXDVrEkK7pUKS4opVECVFudkYy2vY5ND3XJvGwzUklrql4enp9SnbvcyqpeVZIqySWrjCB56rtU0r6wkExqKklRE963JGOXdVlSuXT1d/3QLx8bZAZyA6stJPKWgsoD7BfVMfd7GvjJTE3aCGRTsjy3TG6fcZPsM/oAGV072r6LRNHHcWzqKJa9N8NqR2mfW5Qu6ZSX5j8vhRLvVxupgko+ljCHw9F7sIlAUiZzNt5DyQ5T/UuuKLOXtEmLNsVpKcjo+pI0VKOWAVSIMJWIy2h/B/3l3iOy8p6dMvLColZpzyUlQ9gU3gPtay0YSwmRpz5M+pdR3SdTKEpK+76ckp+c9o9FfT+oQ6kiOpFjXdF/OWL5fbIIrzZa1z/euKfNIjFCq5RPasebk+c6HpXZ+ekyvm6SCnzSnPTRb0E4Nnno626qHiTKYKWUKsq8tnn65rUD1v0sbOlwOHoRCFpkUrR+1tY0qey1dOWlS5WsqlRJmmpELIotBm+FNx3whneYOESmDq2SB2d1SgGPgfW0gDY37akPU4G+zvo7DP6RkR/jf6JEjAveVpe29UH/JDu0ryi73S9Zq1n+AAhjS+kHUekA8DQwk9kP9VtYVlwijy56SDKZtDQlh0iqkJFEISXZRNY+GcemjoQ0VQ2S6lKdyf7SrkWSZOwAos+oaIfD0cuIqwPReE7bk0xJS7agcplUkpOURmU6mW6ZjJQxlVLL7+jn0BeaS1ZLtb6zA6cOkntmtcozizukyCxmhax2tbmgannqo1RdIKKB3+NR3UblDOlilsRoAhElo6YbO9YV/XLqaWwMvGBCV0goP+3SKjmmoLX9qMDxhtkxUNHS1ixPLXtY7l92r4ytmyxHjTtOxtWMV5nnu9BvJdkh6URtObdjU4S1QJqmd70g1z1/lSxOzZOGRKN8eruv6m7GCaS6iY/D4eglmCBGxIWQGdSsJD+NoIJ37q2zZE6uTqbWFuSUHRpky6HVkkmkhKmLOQ97c0nzcXb0n6Nfglm+EkV9vwwFSMrfHu+QRxZ0SjqdlHFNVdJYhTE58vE4+gZDGkX2ntggI9OM1VHJMsKD7ktwaUb146T+70K2LkiA/kh2bG6XQHRoeJN5uXPGzbJCWqIXX2Sygkw5t2MgY2nrYlnctkAamhrlwImHy5b100zMzdvHGuN2EmnL69hEoS0QzdD84hy56enr5NXEC0Zsvrrtedqw53U1JSlVrNjncDh6CaYJWI+ryjCTAWlfW8hJKZWRT1z3qjQnG2WaKmKnbl8vk5rSkkpmzOAUkR1CoQizUbge1m8Bj8F4nNfEWJ1F7UW5d25OHp/fKcvbtbWFA+FRcPQZxjem5KQ9R8nkaoin7kgyOUE0bh2yk08kpeJn1B1rQL8lO+YQN29d5NXJJtvltw/9XFrTy6IflrTpKFzz2SyQSsiUxq1lvyEHy/i6ieXXro1AISkJbQlotLXbtayOTRR0wNoMLU8ukbuev00e63pA8pmsfHPaz22sVvRzokpoXeQdjt6DaQLM+ISJISNpvDrFnBRSVfLhK1+SXO0w2X5YRk7dplpG19I0K9np9uw42dkUUNJ3yjhXtD4CFbv0XXXmi7K8LSdL2kVaC7qDGSocfYYRVQmZPCwpdarbiMoY07+bt81mY2OiAt32scrrhH5LdsqtrgErEygUC1K0l207HZsJqpLV5bWV0M+2vOYYCCipXPOTwYliWh5deK9cs/hyySqR/cLWX5O6VL029WnVn1SR8tfucPQaikWmue1UcqOyVmIKYsz8OcknquUD18yWQekqedMW1XL0Vo3SwE8BYF9GdpN6bonQmpw2zhie3CrhcDj6D+A6/bRVQquJEkoO02EmkylJpTK6TEtSG+NkKulpM0iVcKIz8ICUR+PwROrqGySTqJFkUWRFvk1ShKsSsoiVy+Fw9BpoWksJDAvlsTf8b9ZFRJC5L4tSq4JpUxVXiKOdqzlcSh0OR39EP/XsvBaVlYyaYMfmgvCZOtkZgNBXa+P0ikmZWXhZrnj5UlmWXyynTn6/TKvbXg/nRSC/bjF2OHoPxZJymygl+f0ymtpSVjoTGfngDUtldKJLDtuqRvaf1CBViGIi8uxgi4Do8OOHsB7+HA6Ho7+gH3t2egC6riZrRsvrngZ+guTE+fgmws0d6whz3KhwN2QGSX2ySZWthCzvXFr+BghljcJZHQ5H74CRNzaeg6X9gYR04shRwlOTSUpTdapscigTGlsENYKN8n6Hw+HoR+inZCcoNytT1AQrtAW2ZWhXPQ3ohCenMjkGJgqFnNSVGmRSzVbC72nNXTFLOqXDhwA4HBsJ9LQWuob1wf6lZfbyaNrbQdVJGddYLYlkFFpufXPCztAUUaOwcDgcjv6ETUiNoBVd2ZIycYGngZ8cAx8m1RDZVEKqEhkZVT9K9yWkI9chHYW2iOSaSuVwOHoXsX7WeE9ClrVnJVkqmGensSYTGZxMHMsGSAXLkBwOh6O/oZ+SnXjTWU6vsehXHPc0QJNjwCMBsVUFS2U8WUga2YHmZpXstGaXm6HZ3TsOR28DksMsa2WyUyrZ1tL2LknpWnUmIXWaEMeI5kT5opa6fI7D4XD0Q2w6ZIcULEosVAPyNPCTY+DDxgeUCpEClRcZUT1chgwZJq1tzTKvZabkizn/6QeHYyOA6aaZdY1JCrQBlqxK5Zxl7VKXKsrIYYMkjSCqmJZonzkBjhNS9J/D4XD0O2y65lJaWk8DPzkGPJjqNplI8Us6kkgmVNFKytjasdKVyUlzsU1yiZw7dhyO3kYSD2u1SqFJoiQSBWktlmRRvk7qC+0ypFqFMMEU1EkmR7T1KLHOMZKV5HA4HP0KrkI4HI7+gW6Cm5DhDcOlqMrXilyLZItZdjocjl5FCWeOAiGMvDRdKnodnUxQkJPGWlcXHA7HpglvvRwORz8AUf9FKaXtFztkUnpLaZc2WdAxV1ral+sxD5FxOHoXYSQOsqjyVkrI4qVdsqw9J4NrEjKmPsrlcDgcmxqc7Dgcjj5G5NKBzthYAUVTYpAUJC+dpXZZkVthc/M5HI7egw3T0WWQNGZia+vKqxQmpam2WqrN6+pwOBybHpzsOByOPkVEdRSqZYXpxmsT9VIsFiQrOWnJtRjxcTgcvQmkcOVMIEhcc2deEqmMNNRUOdlxOBybLJzsOByOPkcpUZRUKcWKbVclqqUuVS+d2Q6Z2fmytBZabL/D4egdlCQVGRsSjN1JSrOml5a1SnV1tUwc3ig1STc4OByOTRNOdhwOR58jhM4kIx+P/p+QqmSN/p+U1nyrdBY6bL/D4ehFWBgp3p2EdBQTsrwzJ0kVyfrqjO7jV3ccDodj04OTHYfD0Q9gMWxmUbZpb7Vpqk5V63ZCVmSV7OSc7DgcvY9oegL+tWdFOlktFqXOYth0w+FwODZBONkpI5/PS6HwWstVqcQPHpbsWHt7u60HsF65b3Voa2uTonYaIS/L1Z1Xeayn86gPiXWOd3V1STab7c7LdkdHR3f+zs5O2w7HWZJWrFhh5Yb9JIdjo4JPTpN+fbYsYkFOlGRwaqgUkwVpK7Sad6dU5PvkOy1G+aPs0X/+3TocbxzdclWS1g5+VLRG8oW81FVBdlxdcDgcmyY2q9YrKPNB2YcsQHLY/uc//ykf+tCHuklESAAScdVVV8knP/lJy8s25z322GNyyimnSC6X6y4rThoCoWD9//7v/6SlpcVIB9uVeOqpp+Tss8+WmTNnlveIXHDBBfKlL31JEomEkRfAuVzn5ZdfloULF1r5lHvxxRfLRz7yEcvH9rvf/W752c9+ZnUjXXLJJfKLX/xCWltb7bz58+fLvHnz7BqvvvqqzJo1y/Zz3OHoG0RywbgBvvnJg6dKIpVQhatLZi6fEY2YtqO6QtZVxOi1MuVwONYVqAQplbGSzFnSLO2JWunS/mNodUL7nlSUxeFwODYxJFR53qy0BMjB9OnT5dZbbzVSgFLFI8BDw77jjz++nFOb/FRKPvaxj8miRYvke9/7njzxxBOy6667GtkZP368eUVuuukmOeCAA7rJ0dFHHy277bab/PnPf5Zly5ZZ+eDRRx+VHXfc0a6VTqdl0qRJcuyxx8qYMWPsOn/5y1/kueeeM1LEcfZ98IMflMMOO0ze8Y53dJfPMcqcO3euDBo0SBoaGmw/29dcc42dc/nll8u1114rP/rRj2TEiBF2/YsuukiWL18u73vf+4wUNTU12T0vWbLEyhgyZIjd11577SXvf//77RyHY6NAW6AiBIex0apsFZJ5C2R7dPkDcsOMqyWb6pCt0tvLaVPeK8mqpGZnMtxMRG9UvBhmEBEktzw7HOsLvDn2fykhhVJR/vHkYrl9UZXk21bIb48fLzXadyWSLmMOh2PTgurMic2K7HCrpJtvvlnOP/982W+//Wwb8gBhSGpDHtZra2vlySeflF//+tfm1bn00kvlmGOOsf0QldmzZ8vPf/5zIwYQDQgPmDhxonlS8MgccsghRorYvuyyy+S0004zz0tNTY2RkQ9/+MOy/fbbyyOPPGJeHUjH1KlTjaCcfvrpRlwgISRIGtc4/PDD5frrrzdPEIQIAtXY2GieGe6FfBCwyZMny8477yxve9vbbPvee++1MLYddtjBymAborXFFltY/W688UbZbrvtZJ999rFzHY6NhkB2VMkiBbLzQuszcsPMq2VZcYmMlgnygW0/Kqk01uWCHk2bagai0QR6TiId7XA4HOsMwkf5SV8EqzNfkr89tlD+u6xG0p3N8rvjJgpTFNA/OhwOx6YEuM5mZ6aBEEyYMMHCvCAW48aNswQpIY0aNUqGDx8uRxxxhJx11lly9913G7H54x//aCRg6NChUl9fLw888ID8+9//tnIgP+zbY489rCxIEyDcDHIDmeC6hLCxjQclECsS5T/00ENGSj772c9KJpOxsn/7298aKfr73/8uF154oXmkIFsf/ehHjUx985vfNEKE52ebbbaxa375y1+WK664Qpqbm+W4446ze8Kbc+CBB1r9CMXD4zRy5Eh55pln5KWXXpIf//jHRrRGjx5t13A4NjYgN8ZaVHQi6UnI8JoRMq52giTzSWkuLpJSWpUxhutos1VMMK4HgqRZjSw5HI43AiYmYHqChPZVC1oKsrSLPQmpSZaM6EQC6nA4HJseNjuyA7bccksLN2PMCl4ZliQUfUgF43cYO4MX5KCDDpIPfOADMmPGDPOoQAogEieccIKNm7n//vvlwQcftBC0hx9+2MrDc4PHZunSpfLiiy9aPiYoIA/jY9i39dZbW1mQIFIA5AfvDN4d6kDoGdvkCeFtbAPC61555ZXucUfh3EoEUgXp4tqMNcITxD7qvP/++9v5EC48Rg5H3yKagLo6VStNVYMklUhJZ6JT8kUm5ODIa5UuJzsOxxtEKRn1IypNLdm8dOVUEoslsbkJbNIQy+VwOBybHDa7MDbIAJ4VFH9+LC0QAUK87rjjDiMDjFshPAxygScF0vKHP/zBxvjgwcE7Y52CnscSwrDVVlvZMULE6urq5Pnnn7dlyIe35aijjrIySVwf0gUpgkSxTfgcXpfHH39cTj75ZPP04DU655xzrN7f/va3LfQNcM3//e9/5m3Cs3P77bfbNT/3uc8ZQcIr9YMf/MDC1CBFTGDAuKHBgwfLT3/6U7se4XxMVHDGGWcYiaKueJx4Lg7HRkO5BSrxY4b6x/gb9mX175GF98ld82+RlsRy+eJ235XaUpMkMpxQNN0rUUiZEpZN5FUp8zA2h2N9oc2/jdVJSU7umpmVG15cIfNyGRmXzsq3Dx2qzEf7S5M6h8Ph2HSgOvjmNWYHwgBxQfHHI4JiT+IRMNnA008/bWNWwiNhCZlg7A7jWzifCQu+9rWv2eQCJAjKueeeKyeddJJNXkAI2he/+EXzzEA48LpAJAg5+8xnPmPHq6qqzIME6WKszi233CKHHnqolY8HifE9b3nLWyz961//snp94QtfsNnVIDZ4j6gvEyFAZAipo454jxjXw8QDlEH9yMP2PffcYySG+uO5YpwQpG333Xe3Wdjw6jBOCIL21re+1e7f4dgoCC1Qtx5VlCIymBd5pesFuWHOlTI7P10+NvGrMrZ+vB7VY8miMFVBoqAEx8mOw/GGwdTuNkuIdMk/n++Ue1/pkBW5pOw+cZicvVNOiqlqJUIuYw6HY9MCXGezCmPT+7UZzCAMjF35+Mc/bso/Y2CYPIBjrLOf9IlPfMLGwkA69txzTyMujNmBIDCeBsJBmYEcQVZYh9wwPoeZzhYsWGBkAsJB+BvhchAUtsPYHs7B48IMaXiHgpeFJYSFMDrKZhsSxcQKTCYAcaJ+J554onlwtt12WyNdnEM5ECjqTf3xIkFkOGeXXXYxYkQoH2OOIGyQImaiY1IFh2NjgwkK+PFCm166mBBVrZTDJKUuXS+NqQapLtTKUsbtqDJWVGKjAqL5VE5QzuA+mt/hcLwBJKIxO1JKS3s2KXldJko5GdSAFUKl0aeedmwmQP8KKWxvLFRee3VYmzy9hTVduy/rtjpsdmQHZZ+B+HhsmDmNxDoTC+D5YJ3QsZAOPvhgG+gfPDSczwxnhJ8xpiZMNBB/uXhMCBH77ne/K9///vdtiSeJsDImA/jOd75jIXPkg8RwPsSJRHgZ+4LHCYISvEohBI5j4Ty2IU54rMaOHWv5ITrs534YP0SdA7ECXIN9TL5AKBxjlc4880wL2WNmN4ejb0GwTBReWpOukcaqJknpX0vnUj2mMmZiFuXRTGxE6w6HY72Bx9RES/ud9i7sDshUUZrqVLr0gMuYY3NEbyrt6HEYm1nGdcgAjvWEkC+c31uI14kl16qsYyXix9eUd2Nis5ygIABlKnxohJSxrAQkAZIDwoseNmyYERa8KmFyAPIE4gMZ+uUvfyl/+tOf7Pdt/vrXv9o00L/61a9sVjdC2Bg3E8b3cC4epk996lPyrW99yyYyAHhfqBfXYAlxCUQHcC2ICyFoeI8YZ8Q+QH7yUmcS+cKHh7eH3w1iAgbIF6QOcE5/+jgdmw/ialQptlGbrJOm1CBJJ9KyqHWh7mFy3FizpXkZ6wMZcjgc6w8TO23/i8WStHbmpEv3ZFIlGVpHn+Dha47NB0GPCugtvYjrhNQT4kbqnsB5a8rzRhDqFe4/XOv1nkc41t90yc2a7CxevNjG2zCo/7zzzpO3v/3t5SMrwcuFjDBzGtNSh5fPPsbQfPrTn7aZ1ZiggLE45H/zm9/cTTxCYrrrQIgAnqGddtrJPDB4Yi644AJLeH8IJWPf1VdfLaeeeqp8/vOft3ryOz9MpPD73//erg354Rxme4O8UCagTMLWqA/jeyA09913n4WqzZkzx0gV50FyLrnkEiub2dmYzvpvf/ubleFwbEwkSioXyJaJB2Qei5JIplgt42umSGN6sLzY+oK0FJolqXnJSghboVSQYrIgpXzPnYXD4Vg7JDAYENmeysjSXEk6ElUyalCNTKhNSClZhUg6HJsFMCgTedPa2mrbQe/b0CAqh/HTDHeIk4PgsWH23tWB/Bi5GefdW4jXiXV0ZurG81gdmWGiLI711jNbX2xWExRUgo8JMhDCuvjtmcqZyMLjYZY0wswIewv7mMmMj5WwODw0AeFDIIUXzjgdPEJsh33hOCFo/HAowIvD2B5CyqgfxxA6iMuUKVPsQ2M8EHWGgHGcujPeCFBeuC/IGdfg2uxnvA/bzCrH+CDule1wHmWxTT0djo0GPkFNpaTKQ0llR8lOQf/ShYwUEgVZ2DlPrpvzH5nTNlves/UHZHLtlkZ0CLpRqqPfbklS2YwkojlyHQ7HesB+w0r/8v/P3lkASnJU6/9M98xcX5esZTcbdyEuxD0kD4hCkAR4OA93dw3yfzgPSIAQkgBxVxLixJckG9/Nul8f6/6f3+mpm85wN2v37rX6dut2T3d1dXV3yfnqnDql4VM3L5fFxXrZZ3yXnLvXeBmdyyaaH1/FPIYYkGmQiZDXENb57WSwWiAzIQcSBxLCOoTMgca8HydQpOOA3MUUA2Q30sMLLs6isJxhDjZA8Gcg+eijj7ZrGfAmrpO7brnlFlucnoFs5o27aQRY2SD3/fKXv7TB+FpwPeG6664zonTOOedUzyTnkCOREZEVkf+QB5mS0RuQKbnf3LlzTc5kbUaexcmsbu1I0rvzzjvNCRbneJ88j1ubkn3SYeoGA+i8n1qs7b33N/S+I8sbm4eHxyBEleyg1UkaI7yxRRJGWf0dSVfcKVe9eKk81vawnDj1DbLfxEMsIuZrODbAg1RYUrKT85KYh8fGArIDOrVuffLGJbKmUieHTanIm3ZtkfpsPpm3kxgmeHgMGSDiMiiN19u77777VQVuCAHrDkJMmIqA8M5C7wxmM9UA4d9pNhg0ZvF5HEFhTUPaTF3AOscNGGNxQ3wWe++N7DBXGmLBYDWkCidRTGPAEgiC8eUvf9k88UIsSIdjDFSj0SEt5l0zSM26j+SRqRXEY/oExxmkh8Bwz/e///3mNIs0uD8BoobTLSx+mF4BwcLCiWeBIHHu7LPPNg0TpIclT4477jizCIL4kDZrUTKvnf0rrrjCPAjj6AtLIkA+uZd7bmfdtDmh9/Zkx8PDY4BhTZA2vilJKqMNNmRG92A1ct/yf8pVSy6WWQ3byZlbv00ao2ZtRfW0XhtlKhIoMcoEnux4eGw0Iq1LcVkWl3Ly5RsWqACXk1N2Gi2HT0dgYY0dEV/FPIYaEP4x/0czwf7aRF6Oo40gML8aEgLB+f3vf2/kBcKEBoUtVjFoXdDssGTHP/7xD5tegCDvrHzOPfdc+cpXvmIWOWhauAatEd51uY61FyEIkAc0JX/7299Mm0RcvAXjLIvrCeQFLRFzvt/97ndbmhAx1ldEs3PggQdafiBo3J9ngQiRL0gOaUHCIEAsicL5v//970aavv/978sTTzxh973mmmtMc8PyJMw9v+SSS+Sd73ynxUX7BAFivcjzzjvPnhWSdMYZZ5gmi/nmWBux9Ap54V48BwQMouOQ3t9cgOv4cRoPD48BBaTGXEg7GPehQUzm7oDxzeNt9GxNeZW0lteo4KXn9RRmbxY3fb2Hh8cGw6qcCkHdpYoJJPVB4omNgdhIzxE8PIYaKMsQGKYGMBcagby3gAmZ816L0yeIDfOh0Y4ccMABpuVAS8GWdBDwEfhJHwKEgP+Tn/zEFn5nagNebjFNw5kV5IBF4XE6hYbn6quvNhLllvrADIzF3fkNiXGEDHKGJoctxAOiwVxr0oSkXH/99XLvvfca0UJrA9HA0y/EhjnfaIlYEJ97O++8EB+WKkGrA8Eh/wTeAe/IPRPvw2llyDN5cGSROKTlzPWYQ06aX/rSl8wrMMu2MJcdosa8J65zcM+2uTF0yY4JRMnGRCJ9gRbsoAsvx/NhIIL+6Qn6larH7Su54x4evUEbWxdoeEc1jJYgE0hrYY20da+xMgRcEXK/PTw8Ng5Wg4JYCkUEIJH6MJZRdW4cIRZm03l4DDWgvfjCF75gGpX3vOc98ta3vtW0FSzoTuA32/e+97227iBaHea6oKmApLDQPOsaonkhHbQVOI2CVAA0RhAUTNEgCGhW6LMgTJAkfnMcIgF5YN4Qc3U4BmH53ve+Z+SELZqe2rkukBhMzJhLc+ihh9rca/IBsYH8kD+0PWifSAdTPEzIHGnBWdX2229vaXF/jrvAeQDpgZTw3OwjnzFHnX2IiovrSAvPzHkIEs8CIcRRAmZ3kDZID1ofnGaRLu8HQJrcPTc3Qs3cl6v7QwqsPWivTNtfs3bRX2V9icnaAPpSOcIkZhs19mEgQkG/RzLdPCNdKqgGGS3o9qVAoHFsfN5jhINSwAKirmxYW6ghOWY7ksvUyR0Lb5I4W5Hm8iiZOW4rCUU7BU5TjiKN621sPDw2GkUITVSRZ1aI/Gt5UbYfU5E9pjRJY5iVbFCtZ1Q4D48hBLQwLKzOvBbmxGD6hRddhHLm20BKfvrTn9q8ExZlxyRs6623NscCmGjhWRdhH4Gd61iMHZLBAvFoN/Cqy5yWyy+/3NYtZF4Lgj/XonnBBIyF6CE7zIVhyZHXv/718u9//9vm8jBHiIXiIQcQIUzFIEloTTBD23vvve3+OAJgLg5OECAZEAxM29gynwbtEJ6AyRNaJcgYdRat05577mnPA7gfx3luzOMgJHjnxZSN9Lg/60KSFxw0OGID4UMzhedh8sB9MFVjCRNM43jHmMDh6AAyCAnjudH0OALHc4DNTXi+ohiymp1IhWnAqJMFZaI5bajryiUJo5IEcUEjaRwfBizkooIEUZd+m7Lk9Xeo3wfqIzET5BJC6uGxPlBxS+KSboOsLOtcKgXpTgY5rNHUEPDDw8NjY8HAVDnKSlu3ttOZUMY05qVRWU7GBBS8H3qi4zE0gabCmWE5LQPzeDjuzMbcefYx/YLMQAAgMZAZvLExAf/iiy+2SfiYuCG8u2sxD4MkIdxDRjiGxgiygGYGLQmaFSfocy0kAs0NDgggI5CCNBEgDc5zLSQMrQ7ki3tDaCAkeO+FoPAc5JnrH330UTMrQxsEGeH+aI3c8xG4P5oWiBLzjjC5Yz1IiBjXQvzYMqfIee7lesA+4Fkxo+N9XHTRRXLhhRcaUfrTn/5ky5gQ3D0B281NdByGLNkJY0RlDSrkYEtc1Cexz8AffaH8Q6j2YQAD0M8QaGHPUsjjrH4xm1Wu++wlFcfDY11gHZ6GsNG2reVV0lZptbJFs5m4q/bU2cNjU0B7XNDOdHVngRbayE49zbg15dajengMWTitAgJ37bIbnGNOKPsch1iceuqppvXAlTRzcDDxQpMBwcA0jt+A+Aj0TOhHe4S2CJMyjqONgfC439zDESTCQw89ZPNvmHODk4Idd9zR0uUcID8QnYcffthIxLx582zCP/N2CMwfggDhsADNC1oszMYgcmiE0L6gSUJr5e7p4J4VkH+IlntHnHPEzAWQPs8+BIp7YCYH0UOTw7Oi7SLssccer7jebQcCQ9aMDU0O8jQmUphD8cnCxSul/PQ8iZYslfKy5ZJZvFDiJYt9GKDQtXSlBAtWSLhkiRbykpRHjbXvxVrc/GZ9FLpYD491Ae3t46seks5Kh4ldM0bNkonZyT2ma6zLE2R8WfLw2HiUZU1R5OH5HbKkGMqB0/KyJct+aL0KtOVG25OIOh4eQwtOyIYEYGaGuZUzrWLOCZ7GABP6cR6AlgNzLSbxQ3AAJAIC5AR5tD2QCzQtmHtBQgCmYZATtCKQEDywMVmfPEBuICGQLbylMQeHOT3E22+//YxgQGAgD5AITNHQsLz00ku2pg5xuQbzOI5Bfsgfpmpod8gTGibS4Xp+Y07GHB4WlofcYDIHHnnkEdME4T776aeftmfl+fEUN2fOHMsnz4EJHBou3geaKLZoczB5QyMFoUGTBQHExI9ruJbz5JW5SSBNejY3MGMbsq6nI8iObs2qP9aGuNgu7fc9KJUn50pTXFa6XdQ4+SSyx4CApSFjyUtY6pZo1TKJd9pF6o85TjINoyTOZWwsPjdAhd9jiEGr9K2LrpU7Ft0q0lyWXRr3lhO3fIOWH+p4YmCT8WTHw2OjUYm75NHWUC65d5nkGpvlrTs3yexRJSkFdZLTChjRlvvm2mOIARGXgOkXDgeYJ4PpFhoUApPpf/jDH1pczNeYbwMpwvwLAgPBgFjccMMNJrxjlgZRuvnmm41QoLmBLECS0JBwnvVqcIiAtgOygwYEMoAZHGvroOFh8U2cDDig2cFDG4uIkg6kCScJn/3sZ83lNMQKLc/jjz9u2iN+Qz4wRUODBLgvDgnQ8pBfiByup1m3B+cFkBTID8+NGRzziHCMwPNDiJhThBaL58EJwg9+8AP56le/2qONuvbaa3tcT/PsOEb4y1/+YuQIL3TcB03V5z//eSNXaKxw+AC5452RxkCQHr3f0F1nJ1aCk3iJScaaMGMzjUGhpORHz0e4MBiSjzZ8ENbrHy3UxYLELzwtnZdeLI377C+ZY4+RUjYneT6Pl0891gNxpJ1VxxNyyb//IF0tnTI7t6OcNOv1MiY7XgKt8JlKVjJeEvPw2GiUok65Y2lWLn9opcwan5czdx4jUxoqUsxkleyUNAaLEyZxPTyGCpjLcvvttxthgBTgJhlhm+MQEwR6tBXsX3XVVTbRHiEeIB7ff//9Nm8HQIKcoA7ZgDQcffTRNm8GrQ+AKJx//vlGjJjngyYJhwNoQTCPI33IDgtzOlMwCAskC+0RmiLionVB0+IW9WQLEYF4sZ6OM3cjDfIF+cBZAZ7m0N6g/YHw4AYaEoLnN8AipVzH/XGAgFtq4mBCBzEj/2zR2KBZwkMdzw8BwwECaeNimzyfeeaZdg5NF+Z9EDbezznnnGPxcWQAiYJUuffmtpsTes+hS3bKrLCuOceGH3YD73HrAGRVMOKhIu+daUChZd24DnPHAylK8Yc/lqC1LME7zpDylltJHg9anux4rAci/be6skJ++9D/k9b61TIlnClHTT1RZo6abQsdhsWcZPK+vnt4bCwKlS65Zl4g18xZJQdPD+WUnSbKmGxkXjXr8A6CFtVXMY8hBib4O+0CbqYx0wKIvgSEe9awQThnwj0e23AjzW+uQTgnXq2Qnv6NUA85cBoZvLKhFYIAsFAnRARyANFwrqkxP/vZz35m15M+xw877DAzdWOhUNJizhBmZo4UcSytIXk1oG3B/AxyhWkc5AfNEFohtnhjgzgx1wgt1UknnWTX3XnnnebZjWfC/A4nBxAaCNhHPvIRm5ODhzmeB4JHWgTM7HCMgGc2NGcO5Jn8p7GuvPc19H5Dl+xgAsXrQ56G2mQ1cIzfaHjYBlWtj8fAoKJfAf1aVlloNtYGY9FiKWmjUulcKfWnvkEq2+9s34j5V5giaok09+EhWjuNH+l+sJkrhcfghDanqHfkqoV/lUcWPSD12UbZa+J+cviUY83NebasZCfny4qHR29wnXwyuzX5pa2uHQH8XVUsyp8ebpd7FlfkHbsFcuDMsehytB3HCXyFlloj+j7Vo6+AxFYtg9rfp+F+qhSQ7GwCHDGoFXXTx5JNss9xwDF23e91YX1E6XRaxHd5c79Bki870vPbwcVPH1sbXpney3lL9kkj+Q045kzV1oXe7v1q17n4SZSXnzcNZHj+Wb5iZEKN46K5pDeh6dF7Dt2WC4UA74Jt1vYC3Q8kZ01yss9RHwYuULjsO1C4OTB+omS32VpiFq96+ln0y+al2gozZEd3Ep9aHNj0Rs5j+CAZuMjIlIbpki81SDEoyIpoqRLpnNb/bDLC4eHhsQ64ttU1vFXobmsUSHtnh/KZUEbX1VmVotlmixOgqt24h0ffAOm3WgzZoL1nnm8y15f9ntObFFQA6dmmQ/oYjm5wsW5u1lPHXLz1Ce66Vwu18V95v5fv31t+XBy26XTWFtw16X1Cku7Lv92x2nhrC+l7uNBbPBdejpPES1/Xc86gX7xaJjj2cllQvBxpo6FvzsOjf8DcqayWXwoZJoaVulAyO28jUWOzFJ6bL8GyFdXlUbQC6Hl2E6s2Kon99/Aw2EiPYlzjBKnPN0pJitLW1WZdoo0q9UFj6OExMkBdcuFldFZiWdPRLVkVfBrra+fn/Gd8D49NA7090gHlKlYZgPWd8PqHZUeksgF0h/M+jITA0iSoKZR6aRkoSyVT0qCER4tHRJRNRB8k4eGxNiCBagOmGwpsWRuxylZbScOhh4ksWiKZ227V8yqu6rk4k0VslawJrQn58fBwgOzwb3p2lswYP0PKSndWd66QQtCtQpk2Y768eHisFZgDJWOq/A01qHDhjptQGcnTK0VWdAdSrzLo+KacHid+ci6Br2QefQeW9ixnquZL2r4HkQq71SCxFkIVDJJy68NwD1UbN/aU4NDSBCoLhhqcTcemw5OdjcSr2Shyrrfz67qmFi6dtQWHtf1en9CfiFQIxX8EpQwNTr6Clbg2ZLNmSjy2ScrLl0ikHS0kh7zQ/RKDf3ah71s9qrCSWtYGMBPKpNFbSIM0S3eloB1mt5l+o+728PB4NWg7a39TsD4gOf7SypJUcg0SxiWpt1Gnl0NCjby44NF3yGvZY7Fx5lxWVECoaPFiBJ/AfinUNh05wIdhHzJRMqhCWSDYsUpOD5kRrcqCtEObBr2Tx4aglii8GmHAC0U6PsEd6w21cdeF3uKlf6/rXDqkj/UVSAkHBZqoFTQzi+DAhAkSTBwnlTWtElVYv0HPa1m3Mm7xPc/xeCVi7QyZQMm/8fkJ0hK1aCGJpK3UqhVNy21Scjw8PNYB18a6KsMAE+Ori9Z0imTzKoSWpM4aa98Ke/QjjN1Qxmi9cUBTMS1joPJCqPtZDR4jA2ibaW8SRyhaFlQYjPSQcSEtIom/5U2DJzsbAQgBk+7XRQzS5MFtX43spEE8h3R858mitzQ45o6zdXF7A+dqn6G3NDcFaHMSLY3ukDT3038V7VDrJ0+RoKgNW7FgcRI65Io0+U7iengAKxlWjGIZnRkrY8IJ1ghCdqJk4peHh8erImlXbeDJ2tak3kB2OsuxrGrr1DoVSlM2iZPET289PPoQWqycuTrT420GD+bK2DFFWYmjqqtzH4Z9KIcZqVTlVQgP87YwcazYCLi2UH3QxQ9Z19MDBV4XPtAvvfRSeeMb32iLPNWSCojK3Llzza/5cccdZwtWEYcFo1hdlhV0WcApDfcZ2La2ttpKu2eddZaEYdiTPudY+IpjrIx7zDHHmK/zzs5Ou2eavLhrWlpabEs8fKqPGTNGRo0aZfG4hkWlWCkYv/L4lOcY6fcJjLnoHyYd0pxpluhkS9qxZhYslA59h00nnyDB1tvpWU4mC9cBixvzTJ6Pe1CKtCzQ7uk/yvIjK/8l1yz+q+w2dm85fMoxMkrGSkaFNA8Pj95AY0zrq8Kk9REMHiTtckHFzAfmLpALnoukFLTI3mNL8r59xmsbrK0yk8Y1TjKeYA24h0efAJsOypUj1omwqweiggTtK6S46AUpLV2M4GMxDFW5xmN4ITttK8nO3EEqYYOZNoYqh0bmIS5jMwz5L/p7Y6Hy8NBdZ2egwOtqb2+Xz3/+8zJ27Fj5xCc+YSvppsFqtr///e9tgaWvfvWrtggT5AOC9Mc//lF+8Ytf9Cxs5eA+A2SDhahYIfcLX/iCEQ+CO8+qv/z+wx/+YKRp6dKl8rvf/c5WrmVVXlAul20BKn5zf8B13/nOd+S1r32tBe6D0PiXv/zFVvplxVxWue0PshMH2N6ik9RnUIk1LmseV62WzmuvkvzOO0vD7ntqaacRQ42dN802gzsU+NrFqDxGJij9kRYcG+GpBPJM4Qm5fNFFMq40WU7Y6r9ki3CqZPK+rHh49I7eyA5EJpRuDdfeM0euWz1KyuEoOWxqLG/ZuVnJTlb7LRtmkNCu0frlZU2PPoJSay2LlEfa7UD7fUbwu6U07wnpeOg2aVj0rATd7Ulkj2GN4nYHSNPhb5RS00TzcJ9jTRIVGVl3kfaKEuIG8DcGnuysByAJ9957rxEXCASvi5f+73//W5555hlbdZZjCOUc33fffU17wkqz3d3dss022xj5QLtDfFbHJQ7pQkbe9KY3yT777COf+9znehZ1Qnvz5JNPmsYlvdATWqFCodBDdt72treZVudf//qXpUfarLjL/Uj7wgsvlD/96U92Peff9773yYknnij/9V//ZceIB9lh1d6JEyfaCr4cY4XevkCSbf1DGWXDAQqsFuRSoSidd98h+e6SNBx6sBbyZskqw4lCCraWdjQ6NISbUMA9hhG0SESZkhajQIJyIMviBXLdS1fKivblctzWJ8p2ud0kyIZSDrQD1TihkuuMsuY4wNsfNuCQbU3H8yGPEQgzCY4q2q6izclpHYkZWrI2ORMV5by7V8gzHUprgqy8bpvRcsysvNaVrNabgl6NVrXOrhUlQB4efYHYNIvM1kn6+ByjnE8/KMU7/yTRmiXS0bCF1G27h4kMWvAsjsfwRDx7L2mesZUSnJxplOmoX/7idNzI3RvfecN1PNlZB9Di/PznP7f9D3zgA0ZEeGVOCEcTAjmACH3mM5+RvfbaS84//3zTykyfPt00ObNmzTKzs6OOOkpOOeUUueaaaywex50m5b3vfa+cd9559rujo0N+9atfGWHiXmhgLrvsMtPkrF69WtasWSN//vOfpb6+XubNm2eE6uyzz7Y43MORlo9//OOmYQKQoo997GMybtw42W233eyePANEaYcddrD8E9DwHHLIIXZNX8PeW7q0vfCMdF97s9S97ngpzpgheW3sSmFGcpivmd0mPte9dOqhgOwERQmifNJBBl3y6PKH5bJ5F8vuo/aSY2edIi2Z0VIOITtaaqLEX38lMBcZKrThzlR3fHHyGIGwZpcJ4LpXkVDrQ2LCJlEyGfjDN62QjkpWZjV0y5v3maFbJUZBqOeKdk0U5zU2ZKePtP4eIx5xSWkOlhvYsmnRar/4a1I3f45kdzpcopPeId0sGI1XLs9zhj3ywkBmVfMMqal+9ERe1D+2s/GdN1wn/LKi+tujFyCgQ0AwRVu0aJHceOONpkF55JFH5OGHH5YHH3xQnn76aZvzgjnb9ttvLzNnzjTtzT//+U8jJDNUkIdsvPnNbzZtD4QCAoPZGIB4/N///Z/dh/Qee+wxIyGQHu6FRui+++4zrcz9999v5Ovxxx+3+Tjcd7vttjPCwzH2yQek7IYbbjAtDkAjdPPNN8vKlSstD8w74nnQHHEMMziOkZfdd9/drukv9LRdxYIU7r5Pwq2V9I2fYLaZ2GmydVogT3Y8DFocmLRo5pDWP2akrAcfbLtHMt0Z2XLC1jI6GGPnKDX2T8uPXaNIvPUrfMfpMQKBqEDRp16AxP+a1g89UdE29+9PFzVOTrZvjmTvGc3S0LPCOuJH4iMpmVeZXO/hsakoapMcRphSakns7JDynReLzNhOwsPOklL9GKEI5jSw9WG4By0FzBFU6Y9+Ww9ZU6PdPI2VwbVdG4OvKLxmZz3AK4IsOCLCb0gCc3MgOmh23v3udxvRABANyAkmYgceeOB/zM+ZP3++aViam5vNvI3zcM6pU6ca4eFe99xzj82t4cM7QvLpT3/aSAnapssvv9w0TW6eDnlCi3PyySebZoc4H/3oR02zBCA473//++X4448307u0eRzgN/dmi4anT+CSr5bR2qKWaV8jHd/9kTQcf4yU995bcvooxQDXp5hNlJX4hNrB+pFED8qO/sGBRZTTLWRYZHVltfzoma9K2JaT43d+g+zdsL+5qAYmyOk/1t8JGB2E7HCqynk8PEYSkloBwUnqkmnOVZJAu9Oh2/ff2C7MyzllWkVO3GW05LTO4OUwQ0XT/5Ad62k2Xt7w8HgFOrW85bRkRZVIcs/OkfZbfysNx7xTwhm7wIJUAEYrX5dE9hjWgNTY3K2koeppZ4zs2MFk0GVjgWbHd/3rAJ7R0NBAdCADzKPZc8897ThaHvbxygYZIR4an5/85CdmxoZG58gjjzRCArnBrG3atGmmeeE3+3hGe/75540wof0hQKLK5bJpdtjHixvATA1NEaQIrQ7XQIYAZGbVqlV2nuP8hnQ5MGeH/DP/6IILLjBTO7YE5h+RDvnk2j5HtQBzDxf0j8SNTZLX+5WfeU6yHW1WsE1WtZKfPJeHB6hkcF7BnBztACkflYy0BKNkvEyUckO33PXs7dIVdJo5BB4usAeH6EB6ehpJX6Q8Rigo+j3F39pW9OeBTQBe0laR+qgg4/Jdsu30Zgkz2leY3MFgAXEZcko0pB4efYUGJqFrWx689KQUbr9Amo87V4JZ20smpPyFUpT6lwuuD8M7aBtDt25dtf2uRa8HNwie7KwDeEZjoj9zZNyEfwIum51zAHce4oDpGGZnBx98sGloJkyYYOmgaZk9e7YRIJwBQFgwd8OUDZM25uNg5sbcmzPOOMNcU7/lLW+xY2xPOOGEV5AXtCSQlyeeeMJI0IoVK0zrA9mBtEBuykqYHPgNAcK9NFsXIFSYxhE3Hb9P4ApyTTl15D0OslKqU7KzZhV2dnocJabC4qcnqHl4JAXJyo7tqqiWCWRCdrKWmay0ldfIwlUvSaQkx0WC5LxiNMgXKI8RC9fqgkSjk4x1ZmRUYyBjo1UyKdslE0YlmnTmitvAlP1KkE7Bw2OTEZQl290lwfOPSaV9iWQmztQ2PWtOZVAoZk36tdErH4Z96AU9jQ876ZZo4+Dn7KwDmITtsccectBBB1mAxLCFWGDyhVMCd4yJ/XvvvbfNeeE8jgTQ7KDF+dGPfmTxIDeLFy82jQ7BmahhHoe2iOsWLlxoGiJIEWQL99Ich+BsvfXWNq9mzpw55pzg+9//vpGbyZMnG/FiXg9pcg80T2eeeaY9B2lee+218sEPftBcTZNHAs/GvdkC0jLNS1/D9ZSppGO9T+WRh0QZl2RnbyWxviczW9PjnMPLuufjHg64KU3Khe6bCjAjKwrLZEnHQukOizK6MFZmjt9KQnNsoQXNTHAS3U7MvpanV4pvHh4jA69sfqkbeoyBAT2TDZmPE0iu2C67bDnOHMTgdS2pOUlc4kXVuufh0RfAVD1uXSCFB2+Siso24f6n6DHKHTJI2aw8KkGigfRheIdqS2Mwjut+pNDLofUGc3Z827UOIPyzcChOBdhCQDA/Y76Ncz7gzqOtwe00XtYgJpAGtC/EQ8ODBgftCVuOOxD3yiuvtHV4/va3v9k+pm38/vvf/y6XXHKJeXBDs0N+IDNolb797W/boqV4csORAaZtpEVAa8P92edezCHCyQLEi/xA4giYrbm8kG5fIhEva6AHegq1huyYFskUCiKrVmk+9J1p4DjmE8meh4eWGUzTMpGEWiQwadOapEdjmTZqujRFLVJWsrOkdXFC1Ck21UIGQXLFyJcnj5EKaH4S7IeB+Tih1qS8hkO3GS1H7TJb97W+RKHG0T5B4yVjBHhu67nMw6NPELP83sI5UlqxRLLjt5OAQSoKmbbhyTiVllgGq3wYAYEPTg9NAUgGYQDdOGXBysUmwjsoWAcceXC48847jSzgEQ1S88UvfjERsFKAiOBdDY2MU5xh0oa3NOJCPE477TQjQI6QuDQgHm5RURYuhYxAQlweykqW+I0nOFxIs2X+DU4O3vGOd9h6QJAYCBLEC80TjgvuvvtuWwB1p512egWpIV/k9dxzz7U8YOZW+zz9Bn2mwl13S+d1V0vzrrtI9uRTJJOrl5j8aemmyDNG7+FBYTDPauZdLdDioWVEq0R3plMenf+IrC6skCNnH29az02Fq2uuXtbWh3R74ODiuHN9UYdoC1w6fZFeX6K3d+De19pQe663NBx49rUNvqSvI83e0uVYbTx+v9o914Z0+wvS6dfe2yEdPx2nt/jE7S2t3o6lf6/tHh6DC+47uS1zazEf3xAwqOpA3WAJittvv93mDDMXGLkAucGVmXTZYYvXVgZoN1s5YeXw6qh9pG027XXAoGqmLGUlNTi8yC+cK8XLfiRlZI6jz5X66bvpUb00KOs1Gh/HMn2QXd5F7ftw32J94OLWXkM6Li22btD41eDyANx+Om+uzXfH0vHXlg/grnFtJvsuXjo94Pbd1oXhDH0+v87OusDrcYGCiEc0N/8F72aYgtUWFM799a9/NfM04gAauJ/+9Kc2dwenA6yp49a6SYN7YP528cUXGwFJOyFw+XD7NHg//vGPLT///d//bYTnwx/+sBV4wnve8x6bF8ScHjQ6RxxxhJGZtBCBtghNEh7auE/6fv0OfYbyIw9Lt94/p3nPn36GZJqaPdnx+E9oYYDsEGwuTpXsaE2UFV3LJdsQyoTMFptcdl0de7V0OOc6JYf+qDO95aU/7rMxIF9OU+28N9bmk3dEW+gGUNLtDiANB+JynjRpK2kn0ZgzsJSORzq0e7RbtFUIcWtLt/Y6QH7T+VwbuNbFSxNojtM+c18Xp7f0nnrqKcsXAiaDWuQV1MbleXH5T77QvDNQ5cC7YzCKa127nb5fb8/nMThB+QaUW+b84ihoXXDli+/O4CflkGOUFQYvP/nJT5pHVgZOsQTBVL63MkEdYgkKFg/ffOUERzLUy5fJjpZ2DTTk+hyaj/jhG2Xl9X+U0TvsKuERZ0umeUpCdpQQJWSnb4Rw3ol7/+59uvbbva/0fThGYFoBzqSwpiF++t0Cl5ZLh7q8Lrj4gK1rx1x+XPvEb+4L3DWcq82DQ/oa9smLew73vM8995xZINWSXsoVcYYz9Hk92VkX0q+HfRoVyAVaEzpjkC44wHVgFOQtt9zSjlHYFixYYJ0483bQCvUG7kFcRmkomK4Qunykt6SP+RpmdQTwwgsv2PXkj84ToGmiQvXmUpp0IGWQIcCz1D5PvyHSZ33mKSlddbU2g6HUv+lMyUyepJlAmE3ITrC58uIxuKHFHqLDP+YXWOepBQSTtlhDWUO9JOtWbQpc/Xo1UD+IRz0juA6mr8E9COm0N1vdXAd4buYRokGmHWR9MVzvp4kPXiRZ24v3w8LFrAVWC9KhvWT+IW0l7SMDRWi/P/ShD5kmGvKDia4T9jDtxYMkI9pvetObetYrc3DvjXvTDiOwME+ROZLMXVwfcD2g/eU+DozI420Tr5y77rqrDSa58pDeMlDFu2Au5KmnntrjqKb2+/G8DFiRLl49WWwa8E4QiBm9hwBhPn300Ue/whrAgd+16XoMLlDOAbLDV7/6Vbnqqqvs99qQ/sb03ZAbtpQL6sOvf/1rmTt3rvzP//yPWXhg0fG2t73N6oirJwAZgfJDPDd/d3OUFZauhexoybR2m/2E9Gj7XUGmyUjhsu/KmvnPyvh9j5LMPsdLJteiR3lPtOk5KmGf5NXJYwwc0Ma4+gJ54Hvccccdcswxx/TUXcA7ZtmO/fbbz9ZMpH1CfkuDtoG50rQPfJu77rqrembtoD2jHQLIZaSLMyraSvYZyCEPlBfSZFCF8+Tt2WeftTaXc7XvxT0Pedlqq61MpmNQPQ3IMG0I7RbvhGsIDJJ7suPR02g4pH9TUNJbB+K4eOlzvV3LsXQc9t31vR0H6XO18Vwcdyx9nUP6WrdNx99sULJTbFsp4dXXS+vDc2TUm06XeI/dtEEUCWMaSfJTjesxsqFlAhtuyA4wEwcKiCvalJM+bK/pDPB0yCgsI+y1QJBFiECIR2PKwEJfdxhoB3BAQmeEh0Y6ys1aP18FCA7ML/zBD34gY8eOlS996UtywAEH9AhavL+bbrrJziNo/PCHPzRnLWm49gfHLQgdOHk566yzbH0ytNG/+93vrMP/3Oc+Z8/+sY99zNJ93/veZ4LHt771LVtXrPaduPuj2X7ggQfs/dHR49zlqKOOshHb9QFCBYNAkCaA8PCHP/xBfvnLX9po+S9+8QsTHIBrQ90WjT9xGE1H0CQPHK/NK0LVu971LhNyPv7xj9scTPIOIEkvvfSS7eOVE2EWgcbdA7CF7EHoPAYnXDl3W4gt9WdDQPvC9dSl73znO7YOH+bplEUWB2e+MOTYeXAlLu0R5Y92Cg0Q5WlzCbX2pNW2OVn+OSsVSI8iKNF2F6Xyo9OkddbBMu6Yt0o8aqK5O2f9J0p2JkYTqgnU1JeNAfWJQerf/OY39t4x54doUJd4H9Rv1jREe0qdZ8vgMU6g8LBLm8EgBAQiDRw+kQ71l3YCL7zrAuaItAvk6Stf+Yp89rOftXaSvEC6ICNuvUbWcMTTL6TLfXtHhlxZcuAYeaecMEjO8+Khl3guPm0w6dM2uWenfd155537bcBusECfzZOddaG3QuXgClIterumNu7aXntvcdwxl0Zvxx1qr3+1OOljIH3tZoHev1DqkuCaG6R49wPScNQRUj76cMnqcYRZw+Zpmz0GOxgc1OIZZRAEKbdVMwfrGqvow+JLZ8S6WQjxdGiA+kGg3ri6hSDBKD9aCIRpjtOJrK2+uevdb+b1IbhwnE6QzsjFxyU8rujRiDD3DjLQm7Di0nX7wP1eF2rzBNzv2jQ45gIEECJ29dVX27wBFjBm1BSyQwfKSCWCGOa4HIf0MOqYTtO9J97dbbfdZoQA8sKINQ5ZmEuIS39GTDHZgfBdccUVlhZkEwctkCBHDkgPEw3yADDt5R0iCNLR8x55v+QNoQDtOukgJHCtGzGF1CC4QIogco7sIHx885vfNKES4gH54j1AZgDPAkiLddnIBxop7o8AxXnS5z1g3oyAhEkcC1IjSEF2WPSZfAC0UeSFa9DUM8rLOdJx+SX/aIR4Nx6DE65cpFFbt9YHlAXm5/72t7+1co7nV+YQkz71Bo0nmkQIuCsjxIcMb26yk2jddashxOsaS9LGkbbfImU9l6t0iJx3pnTv/2apP+g0icOctu9oG5zmnjqs720j3lMtqCfU0yeffNLaA7Rd1E8GGmi/+RbUI94Ngy4QEt4Z74s6xznaAeC+G1sGwtDGoMWlfrp2x9Vz4LaubXFb7v+rX/3K2pCvf/3r8vrXv97yhqaa/oS0GKhB6wvhoo1zablvW1uuSNt9Xyx80P4xKOSu4xhtDs8EaAO5P+0TcVy84Qh9Nk92PAYQWvJKcVEyt98h5Ztul7qdd5LiWWeIih96UistbV0wfCugxwaAIqFFAVMIFbf1R9JsJfN3kr2+bKwd2WFxYEyNaCbpTBzoVFzHQud54IEH9tjVp8F1a8sX98BcC2GXeHQ+CP0OrvODRKHd4B7ck/Rcs91b2i6fnHPnXWdJ/rh2bfly13Ifd417Ts4xCkke0wIDplUI8IwObrvttib8Qwww18H0AjM3SAnnAfeGADGPADMQ1ixD84JWA5MRhLnrr7/ejpE2nTYkAwGP0dBbb73V0nEChntOzkOAMPnivoyAox3jvUKWuNdHPvIRIzHOi6UTYtJAKPje975nzl8QDCA7CEFonCBwCAw4qEFI4PkxgUl/d/d+Ce57uePEg2QxZ5N8MdLMyDCjsIw4H3744XYNZnrvfOc77Rrg0ne/SZPvgyDGGm0QO4/BC/fdMKNkAMD95lu7fYd0eXHnIM20BQwwXHTRRSakA8oPa/Ch0TnnnHOsTDBqz3WkA8kmLuT69NNP70m731FRUqPNBu11Pq5o852TIIqNAJW1wc6tni+V339KgqPfJ7LTIZpfrcMB7Y3mW4kOueTJ+yK/tFvUX7dP28X7QdBHi0I9gwzxLahnDNYwgPDd737XyCMkk3dKXriOeLxXvOXOnz/fHEPRjvDu3XuvRfo46dFO0VaireE4A1mQVb4hJsGANpQ2DMLqvikBvNo9CMRHC8S9eF7yC6l63eteZ8/EgA9tG+0rbYjX7Hh49COs4CFcPT9Xui++VDIlPfaFz0pDHJnHFobys4mc5THCoc28bc10zX7p74TlWDkBySKJfQM6rjTZwSQqPT8EIZcRN+as0JnQqbA2FltAs+pGDV0nQgeEcOI6JTpWtDpoRTiGEI3ZAkI8nVMt2cFMjHik44jD2jop16GniQ9xuSf7nCMgBJAeQLPk4vP8xCcOnb87hpDPiKa7nnN0/qRBgNSQVzpWBHbuRRyXlhM80AZBQJjzwj5mWLw70iJwHVt3DSPXdM6Yt/E9IBo8C+8T7QjCCoILpm0QBwiAG60lDbb85j7Mh+R6TBDTGhcHBAFMWNC2QEgQatAyQXZ4r8y34FkRktDMMRfCEVFAWoyk89yMsjNq60ZTicN7xm4fssd7IXCctAGCE+nzbJgksRg1eU/nkTyTJ0ZuPdkZ3OBbEQAk/Bvf+IaVaY5RxghoE2gvKHuYpVHuaA+IQ9mgTECQuY56glMhBlcw6UQDgadXnBMhLKMN5jrqB23GgJAdbUYgNpVMWckO5sc5JTDUZa1rUpTivVdJ+9JFMu6kt0slaNaz+p4CvcgsOmgzaeGV/KAR2kRAMKnDL774or1XtOSANQcxE6X9cW047QLEkUDbT9tLPWMgZf/997fvgGaZ90r9dpod0kEjTb1lvUPaGMybISyYp3Evvh31mDk4fBvm31D3SZe2nkEeiAgmdJwnbQaC+M7M2aJskAbfEDM1yBJpXHfddfbNuTfpuTUcaWcpb/Rj3Jd8MtDDABDtG20LbTplj3k+m61sDAD02TJ+UVGPAQVmvJlyl0RPzBFp75boiMOscaxAdhTh8K1/HhsAukvtAqtkx/b0nwrF/KtOhOV/XwFhgVE7tAh0hHSITASmMwGOAOAgBGGbjgLTJsyv6LhYqJeOEmHadSJMIr7hhhvsHJ0VQgiaAgRmOjeA4ENnx4gbnTST9RF6sCknPmlAkOhMSZdODWHI3cNt0UpAvtC+IAjRkUPU6LQBnRxx6UwJxIF4QBS4BhMKRh3pXCFfTpDHhIvzvB/yiFYKcxpGEck7wgJx0cxwD8gF3qIgFgSAYIC2h2dCeOD9YjdOmrxLtnTUxx57rL135vSglSFPCPec+9nPfmbzEUgTIYa8QrIYFcXskPcEWSAPfCueDVt2iBLvgk4fQYSOHyEFExe3JT3uwftBSCBN5g+RLs8DqYL4QOYoDxAbyA7aKgQHtpBC7stzQXbYuvO8I/KAeR7puVFl3ifvmrwhuJBm2tEBQhJlioBwgoaNcsC517zmNfZuPQYnKEsE6iBlgZF8vhn1jbmBDHiccsopVtdxSsHi4Hx7yj4BgZhz1BXaHEb7qXfMcSNN0mEOCWWBdoo6xP0Q1CmHaEy5L8c2C5Tb0VQnZmn8DDWQJz3W1Skdj90t2albS37qtnqUpcT1gsBac43Nu0rMlTN6ZlNBm8c7oe5TtyAqAJNY6hFzCdnSDmO+yruGTEJWqI+0CRALzErRGkNm+Ba02aTHd2RAgoEN2gbaQr7JW9/6VvsOtDFf+9rXbCCIOsy1tKuYALMQPd+Odg9vaWheKBvcj0ER2ghICb/5ftyD9ojBE+YS0S6SP8oP5m/EwVyXfNNeEohLO0qfwL0A7RADSGiZaYPBZisbA4Dhv6gogympgAGMCxTC5Dhb/c1ilhrcbx82PfCOWZsORwSsIKZ/7Ten7ZB+CfsWdU0St4y2hjCrEfgOrJ4c6FkPjwQ0xFooXHvc0y7rTs9+/8AJKoAOjkDZpjOCzNBxIawiWGOWxkRYRukYmXPXER9hBOGDicUIqgjjEB8EW84j9CLoOI87Vn+oLArS+sMf/mCmFRAkzCDwCobNfrqTIg+M5hGPEUjiYhuOOQQCOJ0fApO7J2SOvCLMkxbxMZVh8j33wGacUUXSdXnh+XleOlSIDCPGCODkg84UzQfPQnw6ZzQgjEBDjPBuxPVOm0HADIdjCBvuPuQP0gcpgNAgsEBCOA+cNzQ6bfeuEDj4JggujJ6zJT6EkJFtRmr5TT4d2UJgIDjtCYIEQg5CCMINggxmbQgj5BUSxLvkO5EOBJS833LLLfZNCZwjLvlyc7J4zxznHUNQEHjQbHEP0iHfCLgQJ94R1yPIci3fg3LDPs9J4DncN0x//00Bb1ZT1EC6NNR6QIPdT3dpq5NY1UbcVoVEK0jgGySHPV6J9PdBCHZCL6afrjxzDEEZUk7dQIjlGIHyT/2iPFEWmcdGHae8IpRTfxHkKQ8MtGD2SZ1n69BXZWR9kSwRoO0ii0Eb3Slbb07ItK6QePliaZi1s/7QtkSzFlv20nlkv2/EU8ov7466y76rxwTqN+0A9ZD3j7kg59PgGzHQwTvmetq22vdJHAJpMuhDGgTaWoKLA7iWASbaVb4lbQbp0sagpUG7j/ac/XQ/wD6g/XB5JG33XMDFpU2ifEHseC4GdihXtJmY6FG+GKxxbYi7fjhjeJOdGvA5rbi4Rtka9GqwMzTeqWM+bFrQ/xb0ZUN12JWIRq+svxFqtCKjrq5vEhk1TgtjRXJ6lm+DhVLihtLDg4YK7Y02V64PZJsO/diS0RG4TofOgUCHRSdDZ+M6PogPI2h0RMRBMGELuJbOBeGda4hHh0NHS3zOI/DSEdFJccylS0fLKCQmXGiE8OZEx8ioH556XCdIGmg+mOvCKCEjjHTQXI/mA63T//7v/1on69KmA3YdJh3sjTfeaGY0jFhyLaOY3IPRQ9dZc5/eQD4IjCwyAsqIIkIE74XRZUeSAFsC94JUYWZCJ84oI9ciyOHtDYII4WKLEAHIu3uv5BGTQtLmGvce6eARLAHncH7AKCbnuS9CJHNlcI5A4HtAPhEO+I1JEFvIB4IpaXGed4k5Ce+CdPbZZ58epwk4QSBgbkReOI9QClFx5yCcfEPyyGg7z0FaBLQ8jDIzBwCtFoIv34ORYeZpoC1z34203b7bbiowI04G1Pm+mqZ9Zv7ou6at1uP6V1vpKGm/ORdrPARa3aVVr7byHq8C3iOBOowmgX2ncXV1KB1cvWMf7SOaVfYpD9Rn6i2gHjPYAtGhzDFgkS4b3GdzwdxM663N0VCs9V7LBstJ6BmJVyyQXPsqCcZP0zjaDhARE2RO636SZebtbLpWB/AOqC8uMCBD20g7irYX8G54fxAC2gt3jPjUezTytEMEtMbuvNtyD66jfWeAg7aPNiP9/t0+W7S7OBVBO0c7wLV8U66nfSHQ1qSvcaBtRwtMfI67QF45Bng2Bs3Q7jMQQzvJgA5bBlxol1j3EXLsrh/uGNZzdvjsfMIe034e1YIei2JZef7vpO6leZSk5GNzruaju2s9NhzloEtCbcQqmTqJG5ql5eCDJLPnHhJlVQjRd13WNiUoacOPrdo/75TMdddI8KUvSTmrghFr7Wgafp0dj4EAAoabs0PHgRcvBHdnvsY5bLERwOmoaFvoOOjo6BDpHBH6mUOC+RJkAvMI4iJQM6qP5gLCgmANGO1HK+K0HggumDAgCGGyhYYEARhTMrzE0QnTuTEyyIgk5mHMH3FCO5oUOjjSYsI9hIK00cggoCNwY/qF0wGA3TfXcz/ShYgRH8HdTYBGWGc0kvMICswV4V1BpDCFY+QQwX/x4sU24kxnC0njvSFMoEFC84Wpxqc+9SkjQuwzMR8zQDp4hDfeA/HQyrCl44aA8Ww8D9oVRmUR6hgJ5Rjfg7zSlpM/nh+yhuDB+8MskE4eQYd3gHaH5wOQLu4BKYJs8T3JM3EvvvhiExI4BlHE8ptn4RugjeGdIAAR3wkbTvjgGut3FGzRBDHHBrKFpg4tH2kTn7xQBnjXmL598YtfNEGFdCBBlD+0O5A0SCFkDBLKN8BkZlNRiEsqlOI3i7Y3a7Jn0gGqUBXxLPx27bE+l+4yfg+gsEFFn51heu9U5hVw39+B3xBYTI8ocwi+TE7nOyOIMnGeOYJuTgUmUJAcyiF1gFF6iDHzTygz1CHSox1BG+jm5pAezjMQutFsooXlmMk6/QylDvpXO3jzJ035gQzre+hcIXLTn6V7zn3S9Lk/JpEV/Zkn6iQkgvmVDNzwnmgr0a7wm3O0y9RH2i3aDd498w7RqtEOQy7Yd/kkPu0gg0sMTtCeMHBB+4b2nLaBtpoBG+r45Zdfbm0X7TDfA60z8RioYXCL/oU21C0xACA15IF2lPaGe/PtKR9o9OhTuD+DK/Q5tD+ub+B+tCsQY54J7TWmj/QT9ENommmHyBP9EO+IZxqu0HfXhzN6ByFoYiyk65EWGCuw+uiNW86UcCsVBmbOspAh6LF00BLrw0aGhhnbSnbqtiJTZyjhiaXz6qul9arrJIMaWLvJUCrmPtjEgzGjJcqr4NHVbd8G5Xf/N8keHusGwgkmBZ/+9KetoyEgwNNRAcwaIAZsEVYdqUG4xvSKjoSOiY4FgkFnhkCNIEM814GyRXhBIEmDjhRhF20F12OXT0fK9aRN/rgWMynuw286T0yyXHoI0JAu4kHQ6Jg5TnDCGMI0nTrCE/eBaLj06Ti5hvxyDEDsEPzpkJlHQH4IEAS0NYw8o61xjgpIhzSAe27eF8IHZne8L94xHTQCHiOeECEEBEgnz40mhbxB8HgO7ku6kAhHdBAMIUgICzwfo6R8LyblIjQAvh2/3dwmZxoC6eE3xwmQGNJEuERAgogxIg8ZgejwHAhHmBTWanf4TWCfwHG8yqEp4h0i2JI30uc3QhcaOEwJEXx4NveOsOVHIIaYQrR5z+4b9h2gLklZSP5WETNgpXnEtjiTmKzxPxMx9h4rt6Gt1nKi7TYr43usHXxnCCpEFiGU+kl7wXcGfE++LQMsHHMknzaAcwjKztwK4u0Is6vn1F3IPXWXOKTRt2Vk/eDWQLONMh1KCGOa8epFEq+YL/mmlmrMpN1zbVB/gPR5h5ALBgloF2mbIIYAkkBd4p3zzvgNeG8M/NC2MxeGuk7gXYP0N+M48/ioo294wxuMwPBMHCdtvinX0T4zSEQ9h+Q6rTLzd2iPGIRiAOeCCy4wIgaZQRPMPehL8EYJUeLeLj8EfnMP2kRIMG0URAvtDf0Oz8HzkQfyxm/Sp11zzzDcMSI0O4Bt8qjJETQ7cUUb7ggVPY24i+nRZyhn0WCzI0HbGilrBQ6Xtktxvz0kf8IRUq5vllw5kJK2gsH8+VK4+A9S/6a3SGnqdJu7o6KY8p7hXwk9Bh/oONKaHTqDdIdAW0JA+GCRNtZIYf4IxzBNcQSAUT+EYTotRu3o4BDo0bwg+DASR4cH6KQQcl3nxTlGGLHXZ/E55pFwHDKBe2fm+5BPNBoIOLh6Rqgnn4wGomVxQKj+/Oc/bySBNOjsMaNDs+PMoxDkEaQAvzGlgtBALjCv4zlIFwHLdRsIBuyTD+7LRGAEfMzO0HigqeH98D7II4I816PJ4Z3R2TJyihBA3h1pYp4K6bFPXhBQeF88OxohyA2aKAgEHTv3gODw7kgfoQCBz71LAJHjeTjGu2ZE0wkumBwiWHIMjQ+APHE/BA++H2ZBkA2IJu+N9CFPkBHy4EC+eSfc170n95s0EXZ4Xt4vW56RcsRcHTRPfG8mq/N+APOdEMx4p5BAzPF4PrSGCECM2uO1b5ORcFgjOpgX01XaoJMdh8hUNEB29J2iyyGivdvkGSOVbKkh7n17vAy+P4HvjRc+yiFlj/rC4Anlm/cGwUaDS1tyxBFHGPlGm0c7QBnAMxcDL1xL2aR+UZ4oO9Rt6gFkGlDOKbvEdc4MGDzYLLA5utq3a1Gw+bdaNuK4INHjt0rp5gulbsp2Epz5OYvq6kl/lRs3kMDABe0NGhnqLW07RABSAPmAbKBdRhvG5H3qGkSE6107B3BFjyaNQRmIKt8GMsV343raSuLy/tH20+46T55oatHEQp74LpQHNO44qSBv5Me9D64nDnMaKQe0a3xrvMmxJV+QG9o9t2YY2ivIGc51yBNtNu03fRmDYWiFXRkgv6RDv8F9hnO91Wcb3q6nrS1OPV059S3ZDXj04fv4Aw5sdONMUYP+iFk9pyLlf98r0RU3688WqT/5BMlsu612psqItJK3X3iBNO+6m1T23Ve/nQo52qlmh7fy0WOQAgHUkR20GggKCCmMnNIp0DnQOSF0I9ymOwpG8jBj41o6OIRkBHlIBZ0e5gN0QHRWCDIQF/YRxhnhcwI6HWXa9TRemTi+NrKDBoS5HeQHoQgtCPEJaDIwncOsi3uRPzo6OmKEJ66B7GB6565BGIcA0InSgWNag5kGAhTnEfqZM8DzMoKIaQQECy0Hz8dIKqQFwQBvQpAfRqHJI2YVCPOQBIR57OjpinivPAv3REDhWckbGhG0W8RBWOF+kFCEEEZrEfgRUIgLYYIEIQgweo4WDTMPRkQRLiF5EE8EFYQInoX3jqYFQceZ7yEQOccFrM+DQMT9eeds3b3JF6Z0xOPdOhCHtAFbfmMKQ95JC7KG22BMGSljrLNDWgglxIH48A0QjHhWBFtMmbg/74h7kSZlgXQ2GRVNz9iK5lvbX0hNBfM1zXsUd1t/Gmg7HtozoQViHobu4zlT22mu4Iy3YvtP8J1coLxT1zErg5zUAoGYusj3pTzThlCPKJO0SbQZmFuiqaUsQ5CY28X5tYFzlCVItCuT/QobaS5LwYix3l//xivnS+Wm86W0+DmpP+KtEu56mEXtb/DO06BdoO3mndDWunrEe+F9A/fuHdx54Oq4S5fjtFW0eaRXC9pH4hC4hnTT++sC9Z12kvaFfNeCdFxeyBvP5fLo0icNkM5fOv/p7XCEPtvIkiRrPyWNeKyFwYd+CpijaecoktPfGSll8pLbcU/J7LqTRG3LJXzoAWqcVkytiFoJKw1NkmnrsIaSa//jg3l4bGbQIdAJMIqPgIFmhi1CBkQn3dEA9ulQIA10TphHIYxgcoIpCsIuhMnFJe309a6TWl+kr8dDmQOmMnTADvxGeKbzI18IUCB97w0FnSpEAk2IexeAPAHM9SAPkApGEREGnBkZ+SAg9DGfhmv5jWaJuG60G5AepMPtY95GOs7chHfNvdx9ecdoksgX79MdR+jg23AdAS0Nc38woYMEcg7iiGAJcYRgoU3B5APCicDAu+OZGUnlfTNvCHAPnoHnIX8QTQIj6gTSdoIH8SBJmJPwbkiTc6TBcwRDVvAAAN95SURBVDHKCwnjG1FumHAOSYTk8QzEhRwxcktarybkbghiZTrQHBXNbAu7sVF5bZ+7H7pN6ubeJ7nFz0jQvkylp5JUtD3HpYzNy9BiW1KSFKVHFz0MtfWCuToQVAYG3Lk00OBi5sZgiQvUHb7zgQceaGu2MAjCCD2DCE4LwVyNtQXSQFO0WaHliRJPaQqw1GhbKeVVyyVuGi8yYVoSZwBA3aP+Uyd5/+4b1O6nwbdzAbi47hgkZG3X1h53abjtukB9J8+Ugdq0AcfSwR1Lw52rvWdtvOGMEUV2eNieoN/YeQd51YBXMR82KkRasSpBqO85qx1mYFNeg7hZ8nscIJWJW0jphUUaTythqN9B++tw/DglQe0MQ+hxbShHUEX0GJxwnYPrLIA7RidEh9lbp+VMoeigMJPAbIWR2PQkV+A6INJCkN1YcC2mLAjimEYgpGNugWYDrQ524GhJACZc3A/hfUPJVRruOWqfxwEChAaHOTkIWsRzZAfBjd/YyDtPb+QJoQGzMPaZI0Mc0uHdAX5j4oO5B3EQWiBIHHP5gCRASDmfBu+F+3IPSAlzrDDv491BQCG0fC9+cxxCgUYFknrSSSdZQCuHlg1TEgiZc9DAvbkOLQwe3DiH5orAviNm7nvzTGhxIFHA5Z37Q+x4BjQ5vC+OUZ4cqYMcUe54Fp6xr8gO/MbabO0hIT5JT6nCXFSW7tuvkfLNf5X2my+U9jv+JoWHbxZZs1Db9k6NU9BoZclpm//KN+6RBt+Y7wVBofy5Y2lQPvi2EGE0p5Rr6rQD5Yiy4eqPK0uUj7UFBmYIkPba+/UbjPRim6F51BIVKzkur1oicXeHZMdMkUzDmCTeAMG1De4d8pvgfjsiVAtXfzmfjg84Btzv9PH0Nb2luz5w9wNuC9h3+adckH46LuC4y58DcUYShv3Txi9/b6t/if2o7vNb/zH28Kr/Mj5sdIDcJGOEWvG0EceONyhJRhv6/OteLwsbWqT07FNKhPQ7BVlp3nq2dKlwFrYt045T4228HNYnqG2U+I1wyHZtDZY7l45Te8wdXxdqr1nXvYc1VJAq6qaij846TLi/LfMatIyU7Fe3ResLuPeb7kRcx+H20x2J209/F4R4bOfpZFgjh3M4CUDocPHofBB8ENYR3hGwmYiOOVXa7MB1lmm4zst1YKTJ6B8mYtiNYzrGvA4my2LzjUkZ1zBXBhM3p03gerethTuHgJV+B4D8Mc8F8zYCZnHkgXhpAgVJcY4SIAOQL+IhwJMuaTKKDSFivgx28JjbQRCYJwPRgFyQLu8H+3RGsiEnpAMZYGIwpkGkD0iT5+M8wdUbNCTck3eO1oX4xMXMEGKIpgdzIEbd3YRwrsXshXcBCYG0YqbHSDp5RAtF2oC43BchlWfBTJDvjcAJiMf9CBCu9773vSaAAq7lOPc57rjjbKIy2ibMlsgXvzFhw26fPJJnpyHEpK0vUNGOMdQ81mttotXWFljKzNHRz16cuK20SlYaljwo+UevkeDG30v8q09I6Sfvka5ff1TaL/qWhAufkqjYofWUtXpIUN8LOxpcndU/yRii/omkiwdP4nBKo3PcfgxDuHLi6hLbWrgyQH1xobZuEge4c/xOx68NlHnicT+Xh/5GBacEequgUlZZQA+sXCSVuXdro6KEbef9pdQyVj+z1k8rFVYybIy0pNcodZYiZUF/k9tNDfqC+Nuz796f+x3wDvkmfA/9XRuPfWDvjuPVeO46h1fML9bzlo6C905cd206HnHWFVxaPflRkBc7p+C4S7c29KAaJ/392XP5cveoDdTFnt/8sQ9ln87646GE1NsYfqBoWPFwO70Fj36DVi/7x3+jPFQ4DdTBvApmE7fbWgrPvihBV7eJqvHEiRJ3dkqmUztBKuAgKJ4IIQhUr2gkqvvpY2vD2uJw/NXOcd9apBu7kQbKT05fF+SZAQwGLMJqQ5yNtGGP+2Z02713vgHCMCTETSJ3x913sE4m9U3Sv4mHmROChgNCdi3QYqAJwPTJjdi6eUHkBVM07l9bHsgXmgnOcS8CgGQxCRVvbJjccZy8Y/4CiXDefHg2V7YJpMXvdP7ds5MHVwecoIbwxDE8qGFyxfXuOuKQPuZYzFPCNAwyAcly3tMQ9olH3kiHvEL6XNqALUQDhw7MK2IiLRoqTAN5T84BAWmQLvOJ0MRAivAARzzOE8gfc2G4jnkSvGvuRV6YA8E8CfLIJG+8uJEn8sc74TgECNM2JgBDwkgbMzJnKkhaEDjIiXPhzcRlF3iPpMf9XHx+O5BH943ds1EOKD/Mm2LCMfOa0PZAuCA/aJ44jxarL0CeDJHmLWm59ZjmS49Pff2pMub090h8/MeltN+bpXOr/ZScKKnsWiN1qxdI3UtzZOHffyXla/8o2cdulWD189Khj1cIqa+wmYIKr1qeteLaK9BH5S4s7BNpnGIGgqQH9d4qKZOLYQPeazr0diwdekNv8dJhfbEhcTcF+pUl5lvrv0ysbUXrMuleulCyYyZKMGZCInjTpFqzSiwKRKR0uih56ZQcEgHlxhhPHwTyocHtv+L32kI13n/s14ZXi1f7e13H1xJ6oyKvONbLNRZqz6/PNakQ85Fw4oVbeSOn9LkMgxT0W71sJj0UMKwdFHgMMFIli136MBUftE2r2OJ18TPPSqcKII0nHierps+Q0aWiFL73A2l8/euksuPOWrkYcd48jXNvoGr0Vj3SHUZ6n7gIeQ4ILRwjDoKME2YQbNx1vXU+Tuh015CGE5pder1dN5xBExvQ96l8lIxA67vjuB5AA5hBbnxZdtxo8H7dO0aYRLDlG2B24sy/1vXuXRqs44AGAKEYIFSTVrpcIKhTHhCambTOPtoANAQItrgdZR/tgHMlSxlDq4IADSBRpOmAoE66mK3xDNwLbYOL4/LPludj8iv7kCAEdpc31nRwQj+kjOd3ixiSB9KDNPBMECOuwQEAmg/KK+Z7LHBKPolPHOKjiUATg8MH5jOhueE5Affh/miD8DTGNeSJNNgnLwTWEmE+EJ7fIDa8Nwgd8xN4N8xr4L1zHC0L8ZnHg6YJrQhkgmeBNLi6Rf65N88DIEhoxo4//ni7lvfEe+U416CVgbRBVN0aRqSR/hYOvEf3XDhqQHPEb74R2iFMDXFQwL1qQdo8J5oi0ue5ID7umfHKRtnYVNByodnJmKCjLbXeC+5hbyNerffW54qbJMuwbnebZB69RdrnPSnRioUSdq2WhrhLyl3dUqgfLaVp28qY484RaRojpbyWkSAreSVHyQCFlntNmxocIkhBdPitQnGOG4JXKjM8hhgQkitahnBNzr/yXZdL172XS90uB0j9gadK3DBeoizfmtKg/Z2158RWqHBgZZArKXMeAwb6V/PMaK2AfiE6YNujtVAhLpNolwc7tN0c3t7YPAYWlKxq12XAGx4jAyqqJ81aoSjd3/6WhLtsJ/HRJ0leO8nilz8puUOPltIRRwiD9fV4+hkgIPQwisqcAsxvsNnHPhqBg1ALBCFGrxHGMEdCsCIeVYw08FaFoIRnJ44RD7itA+dIC0EQkybygZmPu2dv9x7uKOHXJ85LoIyZ9T4qgZIEFZ6QipIRLghi35UVvgHBCb68c77T+rx7vjECKUI1GgkEdcymXNkAbEk/Db55+h6uHPR2b/JFSJ8jfu3W5R/BGLh7urRcOqRBSIPj6ftzLZoVzMYAZl2//vWv7TjEAQ0Ic5LQHqGVgMCwvgwuXbk/AaGc8s/7cOQA0sPcBOaj7LXXXmb+BxkBaI2oewRM2CB+xMebGvnj3pAdTLzQAFE/IXiQAyb3kw+8XnENWiI0MjgMYB832Gie0LxAJt27YXFUPKRBKFhPB3Mz3ImTFkTNaVLcO8bzG4v4se9c0XKOd+eA63DIGnN0eCeOnECg0BqxhaAxj6cWaJrQyjnPdKQN2cJsEW1Wb+RqY4BZKObGtNGJUKNlhEfQDRSFwQTWTLEBKz1RZKKl/mLgISh1SenpB6XjxbmSX/Cc5FYt0CvapTuok7rRW0h2y52kMnNnyW63p16jZYFE9dpiwL0gWdwP4ZbegfL7yrLoMcQA2dHviw4gq/vFn39IwqZmCY98m8jUHROSG2rbZGTGteElI9gx0gHaes4wKuoxYFApJfk2kE+ag1i/jdVR+h7ODo1RCW0zBwfZYdSPBtx1yGm47DHKSaNOZwc4zmgo1zFamAbH0kD4oONhFC6N9KO7azjG/qu9FvJLflyHTFx3nQsOLh2XpjtHfvjNM7tzwG1BOh3QW7ogfT2gU+WZ6VBJ351z16d/p697NdTmZX1AyjYoUIUbtKM7taZMhZWuH35X4lwgDf91lgRTpkv7Fz4mdfseItHxJ0jUkJWGzVSZEJx4Z7wPAs9LYIFBvDNhSsKWkWs32u3eHeWP94xwxMgs5QwzIkZvOYdgx5wJBEXuw9wNQPqUIUadOe5G6p2Qyagzwgz7rCifrh/Ug7SQszHfZyiBGTtxjOcnLT9d7VJctUQaJk0QyY2xhhcX55lMfTX2psOVAQf3rdfnPSMYMxoP0XGaFTQOzJ1x39Cl49IFHKv9vb5I56+3vPZ2HtTe49XOUS4xTeP5AGWXhUgBWiAGBjjm1pDApAziwHGEc8gCAjp1KJ02618wIZtriVebB35DBiD/1CnIkOsHHCAxaN+IT/uMdofFRSEnmBM6rZjTFFHXIUnMp8LVNBolwDNyLXOe6F/QiLHWRpoIkp90Hsk/13At2rFa80VA/aUe84x40XLnqfOYvpEf3gvvoRb0Nbghh0DzDFwLqSMu9+szoG2H7FjQd69/klA9rcfK+hqyWt8CFWBx8BNlGLbSMk18FWAznatEli2UwkvPS3z/ZVJXbNPjkJoWKY2ZKo2HHi7BtF0lah4jlUDbsIrWW24c5PQvglRCpEJ55ff1GFpgRhYa95KWnzAqSPEn75HstvtK5tDTpNwyXuxrq0CA19aE4GDCptcp6TWtn5atIOqUcJiZNA418F2SBWKp4NR/bQwyKr2FWZPhMkHfDLT0N7Td3Pxkh9vRKRDcrTF3oBPALIEOAdC50GESjwaedQfoJHDXiMBAw3/++edbx4Lr0nRnBLjOgdE7TESYuMs9SQ+wdb/pBPH+w8ibuyfXuMmladDZs64CE2tB+hWSf7egE95z6JQcSBPTFjoohGdMF/CgRBwnPLs8ATpCOnHMWngXpO3O8Q6IC9x1gE6TvCGkMxfAzRNIxwHEY8SQ9+46WOIgnHFf1/kDrktfu77gC9BRpq90b4pjfOnyn/5Pyi/Mk/qjTpLgNXvK6i9/Wup32kOyJ75O4tHNkt9Mmh0EMly7IlQBV56w/8f8CIGDEWG0NWl7fkC5Ys4BcwLwvsRxvhfvDKEMD05odpgPADhOGmxxYfvXv/7VBB5Gol3Z41vgKhjhkn00Re4bEAcyxSi4Izzu3HAFnWdc0W+iwlHlwX/JmmeflNEH7i256buYcJYJeZ+DQ6VOecHVK2UKsIAo7o3TpkbD/Xv1NagDDv7d9RNwlKevFu+YFa1TtIAJ0UEYrfaV9ot/NOycTM6B5BMxOq9HS2Wtp9dL6bnHpLR8gdR3tEle263usS3SPWMnGbXtXiJTt5egeQINmgpNmg7f1YQqvfcAavQ9Nh0qqUhQ0VZbyUtQXCVdv/qEZPY/TXJ7HilRDi2yUuSyynf6mbusrFWksXWlxGtaJe5s07BaKp1LtLl/WY7z2Pxg4CHxsYg1DhJbIN3ZRhm9ze4ST9xSMlX5Y7BD+4yBITtu6/ZZcI9F3XDn6dZTAE7ghIiwyjjmBIzqMbKFMP/lL3/Z7L0R+ohLJ5juCJ0wyqrfjOAxwZV71sbhWia4YmaCqQSkgmOYobACLftch2BZLpdtlA3hBVIB8JDDKKDTqGC+QTzynF6HgeOYLLCQH6TiyiuvNEHYjYRyDWYbCLmQITfJFr/8ECT3vkD6GdwzseVd8hw8F+5eEbpAOj6CNvfH9p77Mers0sAcA5IGiXTv1G03FEZ2CGspYVSd+JbrpPPWf0jjXvtIeMKxsup735a6qdOl/gQlP0ryMsHm6fQgfrxnzGUcqeSZeY98F/YJfCeOud+QGUx4mM+A+Q7aHeYIYLrDOQgS1zBJm3Qg07x73jHlBTt8bPUpd5Qnvg3x3D0c2HdllYBZGyY23MPlZTiDos9cSXnuaem88goJu9slOGhfyR1ynBWyUqYidYPEvhuCinkX34nv7FwM841cuQLD/Zt5DDFogx1bkUy0O8CVUHgQSwFkmbRs2hztE/UYe8S3mHoxJEnisp4tS1dZY61eIpmFcyR+6gGpLHxBchUlQWEoUdAg4bTtJH/820Qax1oaFb1LNq7T/kLT8lxnSIP2WqKSFgn9li89JoVbL5XgiLdJOGUbJbJaBrRtzJayEmcx1e0Swezx3islWjxfymtWm+ZQG1BrLz0GDlTFZK51LDk0t3FeloUtMvrAY6Vpn8MkCBNvkoMd2tdufrKDlgXhkNFOzH3o8BEuEQhdVhASMIuAHGAfjjtVhDpGx9HsoK3A7ee5555rdsxoUZz3ITQxEBsESLwSoQFhrgRCLB5yuBeCLWQJm+377rvPJoySNuYNmCxgc43WBTKF1gPhk3MIruQNEoKJBCQL0wPsv5lkipkGz0Mc90wOLFCHW1VMmZy/e0w8vv3tb5s7WPLKNdwLgRfhmMmsxMUUiuu5HwIv98H9KNou3hkBwRlTCdyVfupTnzJtEe5gySuEChMPZ0LDgmSYd6DBQWPBPcgrGinIlSM6rLbMOhnuuTYU9jn1suSrqpDnDqRQWbpUoquvkvKzz0v92WdL9z3/lHj+Imk88XiJ99hNK9MrzUH6C3xPbP4hmu94xzusbPE91gbeJcQQD00s+Mf3wFPTNddcY2WFScN8D1Zux16fd4zWB9LK/AG0bhBp7kFaEGtIM++Z78p3ptxyD/Y5D6GmvLMQIuWNydPUC7Ax32cooaLvoHT1ZRLddbfUZ3LSPXqihEe+VjKv2VNyZT2vnWZ2kIwGUx/5Zmxde+D20xju38xjaKGsJEVLq/0zrmPFMzFpS0audB8Na5XiUHzNqsViEQH9q6Zj5zNSV+7QCDkpBnlzU1uvwm/41P3S/cT9svTFp2VspUNaSqulLVcvpcnbyOgt95LwAK3TuQbJBP+5UrzH0AFcxRzJtL8oxYt+IvnDT5d46321iNAOainRwhM9cYOsuP8eqVeCk9fykn/t60SUDGXGbSFS1yRxyCDr0NAcDGdQ1wkgGeKgxgf2DdHIDgVoX5sJVaD/cvV3v4LOHuBhB1tuhMmDDz7YBHi0H5AMAr+Z5IkgAAFxE3sRFBFIEcYx/SINhEU0KQj4pIeZCEIGQiGCIgIlZkcIsNwfl6DYYHOeY8yvwN4ardLPfvYz82zDb0y7WNuAe59zzjl2nOvJO25LuTfEgJWOSR97bY4jtHJ/AnACDqZRjPRi9kZ8hB+AeRokBCEXssb15AtzOmzGEZpJGzt3iBGaLbRAaLc4jhcgyBHkjrkdmAMiCJN/8sCzsrYEhI6FybB3RytGIA3ioIlgsi+kDnNATG8QoploDNlCY+FI0obCqkG1LlgVYT8d9GAln5Vw0SIJn3tRgrHj7X3F+vy5rbaUouYpu5k0O5AIyhHlCUKNCSPzLjAvSwccBhCIz7tHMwZZpeySd+bmQHwoD4zm49QAUs/7PfHEE03rw4KPEB60OnxjgLYQbRCkleuJA1HlN4SIQQKOYQoHQaWOMKGbssR9CUMViFDJjj5HdR9hyc7ohv1ypShdl/xFclntRbONUrfXvhLt9xorHwF2/tQ5ygp1zl1vr0T3qsnbATvWv+Bb8F1cWNv3GcrfzGP4wSYdU1eqHpes7liVqf6jfmKWpFuEngCvWSa46kXmUCArmXLIXwkzZU2mQeNmJRsp8dF6iWfN1kkzpXn2ljJm0mTJlQrS0d0qDeWKNC9fLMH8f0trQeNmlezQ52iSsQpTEWlbHU7q9stIWgvaiGqEGqy9ftmVdomvgxsO966Td5dIO1p29K/7HhyLmNQ+5x6pPP5PyR55pohpASpSpsx0tEt80VelrrtT8lNmS/6Qk6Rzr2OlOGayhHVabpTkQHQoX1YGfRigkJjjw2kIdkzrMhOs+M60BEMBX1H0O9lxJMcBrQUCHgHhEQGPgGCHgM8kVEgLmgmEdoCQznUIfQj7AKKEEIkgjoDqJr0S0MowORigISJNNDsI99wHMxNIE/MgIBdoeTAvQyuEwIvAD6E566yzTMsBIWE9CdKAQHFfCASj9wiveAIibQgIhIzAvB7MlRB2mAsCmUEz5N6HE3QgJMyPYf4Rz4y9P3M30AKhMeI+3B/hm2fmPQCO77HHHvYO0RbxjJgAMtLPM/NcaLAcgUKY5pnRinEdGgYEacjOe97zHvOGhEDOu2BVcOKRL/IPNkows8qQBBX5/vOfNoaVbE6itnYlO89JhGA/fapk5j0t4ZTJEkyfKZnc5pmoimaL+TMQXEgE3pjQzPAO+ZZsCbxbApoa5pihoWR9EL4RZRDPTHwLyCTlh/cHweV9oqGDaOOOF0ILyed7QT75DSkmHd47gXdOfADxdOcgSRBdvrcjohv1fQYNoDsIMlpK8OcfJJ58gki3+ljYDOfmzZecEkmWXmjfSd/l4YdK2NCo1+jzqzAUBSxlmNPfjE6DZC9QQSxxY1otiQP4mvhG6eDhMbigFKBaTZBh8LZEO22gvNIVuGDll7aHUG3d9ZApV+1a5pQm+0ngZCAM7USBCr3jtpRw692koG2/duwSm8lTRbJLn5HK3Aeksuh5KRZW6LGSFPM4lwiUQEGxMHdL6jOEBXO7ZAFLhG3quvavGpgzQh2jtyU2T/JKSSSBO+7DhgXeMd+AvyX9tCGuiCv6rvWd23pJeiy7ZolU7rpSym2rJDzsrXpOv0q5U2TxPKn84zKJujNS2ekAqXvtyVKZuZsS4lDqNJGMfnPW6OGb2wR4CpUPAxSot0ndTYIeC/CeR52nYg8NQHY2ixlb+hYI2OVyskaDE6Qxp8LkChKCeRUaGARArsOEilF03HWiSYGMQCwgPmwxYUP4RPjDgQHaCUzAIB5uPgMEAgLEytT85v5ci1csNEDM5WHdB8gJpADzLTRMCKVuns/f//530zSRN0bemRvDaD7kCxKEGRokjbk2CKgIztwHIsZIPPOGeGZG5hnxh1jxGyGXeKzHgeDK8zPRHVMmNFh4O0L4xpUqmiHIDvHQRJFnNEyQJAgh76RWiOI5nUBMviCQf/zjH+2ZIEEI8rwXriUfOFCAmHEdpI73iVaoP4QzM4mItAx0rZbuv14q2bnzJPvmM6Rw6d8kO3mKyOtOktyU/3QQ0R/g+SmHgGflXfHtXNnlm7B+CASDcsh7gagCyhnfmDKCWRukBwLJ2hwQZ96lK+uA78ExgBtbvjUknHu6b8V55pGx2CH7mCYC8sZvvjlkCc1bf3ybzQlesQUVXMzG244xuVUFmlKnBA89LHLr7dKq36PpiOMkf8DeUtb2gZh0rd3lWLrDnIzVA6z7TsnKRHh2Ym5ALKF2wrE21BS15O16eHj8B+IurXehdHcpKWnQymL1iVpGW8Vvtptegypat/HEBUrWLFbMdXWwcqEU7r1BSku0725bKmFn0bwTt2qfWGoZL/Xjpkt27BTJb7uNZFomSUZJUJTLawuAAIbGSR8hinWr6QdJ+2rSuDUU9qcaQPW8++mxAdCXpm0zW9uwV9G+PEQ3qG9W33mw4Cmp3Ph7Ka9eINlj3yXZKdtJ4am7RR69TYLWNRLN3FUyp/+Pxk40hWgDobJczxIV/MpqOkO8a/MYJFAZafOZsQGENMgK5ASTMMyvCJiOMVkewY0RbLQYkADiYcKFC140EEy4RwOBAIobV4RKRtg5h0kb2gp+Y7pF+pAPBFi0MhAZBEvIFkIsgiRCPfEgR848DeICgUGjwxwg1o4gTxAdPHNxHRootC5vfetbzdwLYgUpw7wJwsBzQD4QQtFgkSfyxj0wjXrjG99oJk38hryQv1NPPdUIHs+OCR0kDjM3Jq2jPXjssceM+PAOEZwhZZgyQV54RkgUz0H+0Cy4gKYGQgNhIT3yhNkeWgRMsNjyniCD5IV5UuSX4/zm2blHfwnUrMItOe2sli6R4IV5ktl3Hyk+NVcyKsCG228jgb7HzQG+O4SDssT3QAvGPiTm3nvvNVNDtCpoc3gnfGe+FWST70aZwFQRYo7mhW/FO4SUoOWh7KHhQRNI2eadU85Ii32u5fs5czk0S3w3vgHfnO/NMQL5ocxhbucWGuyv77M5QBEwTskj6HMku/r9dSdavkiiu++U7OIFUtlmO2k44kip1DWYaUzy3GWZryTxnytWy9SWZmmwq/V6TZQOE4JjQpDGRb7yZMfDYy3QCtLVIfLUo6tli+nMmaEOaaUxksOWumXsZJPAAAWODKiP2YiRCBVzgzqptIyT3BZbSTB5hgRKcKLcKOlgodGupZLvXCTZ5c9KsOhp6dK+on3RAiktXSSZNUslaFspYY6caj7NtK6sfWRZSpk6vQeujXFnnLg0ThZKTQW7yocNDbxPFoK1fQ26q214xsgrywTIPy6T4rwnJb/DHhLs+lop3/JXqTyp8pF+7nCnQ6Ruv+Mlahpv6ytltc1G+5600ZqQljEWt8UhhiXs4bGJ2CxmbABygmCC4Ma8Eky0EOQgM5h8QSQgHZj5IHRy3BEiAkI7WgbWQ0B4xOQLd78I4ZAY0sBkCKGTkXG0LgiSTMRHICRNjjPnhd8QFFYOx2QJ4R4igdcyyBPEC6EUzQzkgPyiMSIOgi+mbwiuCMYs9Eae0Ugh0CKEMq+CdIiDkOqEUPLKe4DssMgdZk0IuZhGQToQoiEtmLDxvOQfL04I3pi/YerH86fJDpoffiNw476Y9wvRQmPkAnlGQMYrFESR/CBgo7lCk0AcNEQQL+6JtgdTPbQGPIebs9MvwrS2ZYzioB7NtbVL5Zm52hDuLKXFSyTT2i75rWdJZuKkJG4/A1KL9hAyjjaF7wB5hXhgMgi5RftDeeQ7Q0wIXMdxvgflmvcEKYLMOk0k88mOPfZY+34cu+CCC4z8oq2BFPGN0RxBsJwDDkwK+c4QJraUQWdqSDmHDJMe5Yx79sv32YxAjOIJnHKc/bC9S4oPPSjxE49ITst2ePIpEmwxLYlXfVzKz0OrV8kty1dKVOqSnVvGIjtpx5mY1iSLIEKdklFIT3Y8PHpHWWXUJx7qkCcf7pRtdxotuXy1kkFyrH3pG7JT0rQSLW6s9THUFLWGMjhBO1bfKDJ2smS22FrCmdtJoO1dvmO1lLUfY+Q/E5clp21iuPIFyS15UrLzH5d43mNSWvS8FObPle6Fz0lppZKgMmvrxUqmcElPG4D/OBXLkUVMRKeNSQRqHzY0YCBc0Da4oqGkoQuOqe82Z6bH4Yp5Et/2J8mOniDZmTtJ+1P/krq590kwqkVy+50gud2OkGDcJAmrWjhbsymIpBKg32FdHlfKSNS32B6bjs1mxlaL2ltCbPBYhccxTLwQrl0cZ16FORlCOCPZaGAYVUcoRBDFYxuCKnERDHHLCxlBEOQ3QiTaHDQ1NKgQBK6HFGG2hXc4NEsQJ0yKEECZdA4RAAiWjOxDJnBPjFkc5kpcg/ALYSK+uxfEA4EZwZa8AK7FgxzzLiBW7vkwbyMNzNjQHEGqEGohN5ASSB4EjwUt0QiRDr/xUAdPhSChVUADxGR4hOI0IFM838knn2xzfngmriF9NGCYsGG2x7OTJ8zltFxUr+5f8ArsPVhDWZKOC38vdTO3lLgSSfn2e6X+oP0lOO74auz+Be8QssL7oRxRTtiimaOMoW3jXUESeX+UUc5DJtG8QTgh0JQfyjBe9viOlAtIJU4fINt8T4gk5JIyBKEmbby2YfLmtJO8FzRLEHX2IUFsyRfaI8ow5Yj8gCFNdhjVQ5CKQyUvZQqDkptQui+5RDKPPa4dYUm6Zm8pTW99j7kqxbY/o3HpGud0leSSZ16Qp+oimaid7k9m7amdphapMCM5TZJR3kRMy4rX7Hh4rB3d7SW57Yp2WfxcgxxyYofM3mWsVphkoAAnIFqbqFBJ5E1BpaRtWc6Sq6iQi6YHMpKIuI5Mcb/QaEkyS1UFYxWks1G3ZF54WioqUHetXipdK5dL3LpCGluXSJ32IaFbpJR+RfNsZrEacKxgaWfcPRKTKe7qsaFQilrBf1pR21k88PGOtb02AiRSJ3kpablpZw5lwwSZsOU2Eh3zdilm623AqU4b4lCJaHe+om00sy6NxprmDY2OfRg0f/qZODdQMNlE4fpW99thQ/tc13/3BdJ56c++P32f2vwjgyAHDQVovq3mDyh4YQiPCPG9aRA4D4lAsAS8cDQizJ1AiOR4+hyAFODBDQ9lTN6HBKAFwUUwxyAYkCNGyAECJWvfsGYPQi95IEAAIFrkjxF2TNXIJ+cwhwMQHwRXhGTyT34xSYMcMSeI+MRFQ4QGyq2eT55JF9JFugBBGNM0pxVKFzTSYM4IxIW5RGgdAO+G/EDmIE2QvHTA3AmyRlqOvDmix1wT5h2lQZ42G/RTM2iojyqR5i03baZ0LlshQZ1+F81vpbWtGrH/gZMBvNJRdk4//XTbEig7jlBAUvCihmbOxUPDCCllDg+/ec/u27Fl3g7zvPjujsQ4cN6VNd47ZQ3NmnPagcaPcsI1eOPje7KFWBG/towMZSBLIY9AYJBAtCuU6Kmn9VgspVFjpWnfA7R+MTbLaK02snoBFOlZLdsL8yL12nlOztfr1bxPUoQUWRFL/mgY8MbOw2MQI5svyuQpuH1uk+VLClKiK7C6Y0MRWqWsNm0ymNvBhAxcE9MjhZauCrwqMNtcO5VyK5ms1u9kPkd9GQEZQSuSrjAvlW20Pd7vv6Tx2HfIxDd8QCa/8X3ScuRpkt33GCntcrB0bLWvtG6xh7SO20FaR28jrc2zZE39JGmtGyut+RZpyzVKe65BuvIN0q1bHzYsdOp7W1NfL+350VIINWRblNw0ieQnSbFxkrSrPBNoIzxu+51lwuveLvEJ79Uy1SANlUAaVVQLY23ss9qGowmKtQTo8QyeaKzN1pKGagfNvBHUgQH9quub2Xf9LL83Fpty7UBibTLGUCE6DgOi2UFIA2gyMNlCiMNRAMK8m4MAXNYQ+Jic/8EPftDOI+BjNoSAjzkc81QgAcQnuAKKQEhcSA5CP4tnurT5UJzDMQLEh5F1RunRkLC2DFoQ1jhhjgUj7Ew+R9BlLg7uhZkLw3W4xEbD4/LqPLkxQs9zQlIgF8RzwjRmS8zbIF20UpjGIUCTBtcQ0AwhgKPFIaBxIQ0EYrQNrLuC1oi4EDTyz/vEhCoNCCFOE9Aq8Uw8M1oyTAff//7392iCuBagbUDLtFmgryzivWlx6NYOsP75p6X1mutk9E7bSuG+f0lm/CSpe9e7qpH7F5Qx3q0D3wZND98Ez36YrmG2iBaMeBBl3j3nHdHlXWNaBhHHBbhzYAA5oYzz7iHQvF80NZBWvhcOLyj7kBvIExoh8kO5xryNe/D9AOWXb4e2abhodqzuaIgC7VwiDbFSmmUvSeW8n0tHU4MEu+8uLYe/1kgP83jCckkqSnBYnfvXLyyQ28sdMqorlpPGt8gpE6fbqtxodwLtMMMYTRF3SYi+h4dH74gqbbLombz884blMnpMnexz1BgZs0UkFUbytX4yu6IvRgzo/Z05Gdpcek74Tpwpq/Ab6FG0SQjFGk+joD3Qs3pr2gbT20hR2zuqdY6tEqFI6zk+2DiW0bZT1rRJ0I5pq5K2QrdUOtdIVO6WuFLW+CUe1tqcviJwIwqZikRozKN6CWxSZMmIaZQdLUFznWS6F0n+/pu0jR4jwV7HSLDHIZKra9HXDYHR7w7ZCfU6yAwf2tLUr8cHt5RSRGeAPo/1SQonSxJq+9j16XN7u66v4OQP5Ir+uod7D2yRe5B13DvhvkMFmufNv6go4CMBNCos6Ml8CEy+MPVx2hYH90ExD2IODsIhLxlywyg4L5+5Juecc47FdR8iDRwccC+cGNSC+SwsBonLYK5D64NzAubzcJw5GxzHNAmNDQQIDQrmSbhwvvLKK81VM3G4N0IyhQJSRn54NtKBNGEGRX6Zx8HcHcgapIjnwpyJNFyAzDF3yLnphlDh8Y20eX40ReSHe2BGh5tkNx8pDczqENZxxoAGimsxf4PkpE31IHoAjRSexDYL9DPhRpROrF3ralNnu3Sd91Np2mMH6Xr+WYlLGWn86EerkfsXvPM0INFu0U/eDe8ZU0LIDHF7G9WA7EAomR8F2XHzbtDC8Zt0IOAQHuZjYermygNlFLKDOSdlgu+M9g2ve+QBBxSULwAJ4hzaIkw5gTs3FIHwQjnIa7PQpQSlrhRJ+dqrJbj/DilNmCHBicdKTutfWclQvkwDGymhKZto892nnpen4oLUlzPyxS1nyfTmvMovTHTFG1tiFmFrgXiy4+HxqojiLmlfmpW7blgha1Y0yX5H5WXGjgxC5LT2aN+K6VkfyDeYpdncD9LUTkBrqAZ6Ad03FS+3CbSdpaZrwABF92lxEZZjM31jnyu07dBtOeBaPUZKejAHAdJzAFIVs8olsUm0B/weuu3mQAEzYtYACCNcC4T6fVgogG+WtLExa6L982KJ5zwqlUIsdQcdJbkDTtC4vHsVlmP097qv3zr9NawLs+9RDcn/AQF9vJMnnVDPb+B+rw+cXNHX/TPpOrkEi5H+6v/dO8BCCTkTOZjnd/frr/v2NTSfG0h2iEnQ54tQN+qPlx+V4qu/YO0eHgqmmqergis+NjlVt6axFkbkGN3TuFp2Vn3u0zJu9mxZ3dgi8tTjMupzX5RMrt4moue006J5jDNZmlj9l4z09Ud9o3JDMFzFhpRAZBw4RkijrAQFTSGND+aBmCUSB3KDNsY5G8DDIMQUwlSbBqBKEpgDxJwr9iFZxGWfbW/XDVbEMeKNdozVPCPPsMccmgSMskYqtISSXbla2q6+SnLPPinx7K0kq0QnO3aaBLiRzpato6Tw0N+u1IQ+88yTkukoyC4zp8oHJkyupufh4bHhqEilHMvzc4rywHUdMn5at+x37CSpH5uVbGjj7UnF9fBYB2y5tO41Unrgainff53k3/hxkZnba5+tZQlqpI3/ZlovfK1Ii77094D+meNY5DDAzpQJN0jOVAemBDA4zcAm/TgDk1yDBQb9PPs4dWIgnDgMmjIHnP6ac4B4WAAxIM5gOJYcWPswkI4FkouXBnlCnsA6CIsfZAOsQViWhPx897vftTRRBvAsBCyMcI6E+T3Xf+QjHzErIeSU3u5Bnllon+VPGKDlmZycQXqY0BOHtJBdIEIMmDNFxMUj3cEom2ieNoLsVGG2lXrANtUWELJjqmkPDwWDNC8X+4QMuyJEKeEc3nWw1Q5M8o2l7Vtfk1H1DdI+aaLIi89L/Qc/ItIyWgsrxAiCA5i2qLSHg/1EdoCbv0TlpYFAw0Z1SVfm9D7n0MIAR2Q45o67a9Npra1hc8GNJkG22Hfx0/cd7LAlQpXIGLQAkHNW0eaTs1+1UpGoou/r7jul8M9bJN9Zkux/HSflPffWc0x51XNZSFEINTITlwXFgnzhxWeleU2nnLLrznJUQ4Oe8fDw2BiwtlUsRVk2Lyu3XLRC6lu65eDjJ8u4LVU8ZT4Nnf3AT/P1GArQRrqCWWLXMqlce5EU6nLSeMgbtC+fJJUAKTGQ/AD3YfSvDgj2kAjMzbEUAjhqYooBVjmQmje/+c1m8UP/DWlg+gCL0TPHGi+8LN8BGcJC453vfKdt8cILKSI+MgD7EJoLLrjA4jA4ink8WhrICtve+nbyigyAky0GU/ECe8011xgRY5oCUzUgKlglEdfNy379619vg7SkCVlBLuF8b/cgr1gYYV2FJRRpAOJDnHC8deaZZ9pcb+QQjrNeZO06jINRNtE8bdg6OwiviYSq/01oSR2o/kri6B8fRnxIiC8Niv7mrxUOtmKmBibg6g9860N2mNQYzH1Kylp5c+NGSbZTyYZW3nJjg7B6doDgb+kyxkiFrabMTj+ASkulpoFw5KW2Iqd/u/O1BCZ9nECj5Y6587Vw5wnc2x1z6O2awQp9CiOmvBXMUCgAZVv0D088SVnAh1Ju/ovSduc/pHH1Mgkr2iifcaqyvEb99vqs9j955hJlRr//go5Oua29TaZp2ThCyfHY6nvy8PDYGNAolyRTyctTD7ZJXAmkeVxexk8JJQhpi6iznux4rBsl2mva7aBJMuPGSOauKySqnyiyxSxt+xn9x55jYMsS+UNgZxCRpSboZyEikB6mKnAMh1EQC7Q0zOFFs/H2t7/dCBCkAK0N2h/MyTmHtgbCRBp41mUKAeng9ZcpDwxyskwJmhkIFHO/sdogfQgR5yEzaHHSwR0D3Pc3v/mNTXNgfjBTDyBJaHncVAUIGebx3AtzegZuISnptGoD6SKboMWB+DDFBIIDEUTTw7shTebXM/2DY0ylcPKMw2CUTTbY9TRNHUBYdY9jF3PA9hFo1js5j2EOFhmjNFjoKf8YrKWgJ20tlAq2oVmpPPywFK+7SnJ1WpaiBpEjXyvl3bQCh5iuQYwQjlWopeNNmLVelyTV13BVw1Xe2t/rg425BvR2XVqzM6SAKsZs6pNnop3AEYFrUCI9F5WKUjjv21Lf1iZddfXScPRREu97mIR6zkgzPk1t0ir+2GJZrkldtWCR3LxmjZw8ZbKc0jJW6vN+Xo6Hx0ZD2xwm+ceVjFzxy9XSsTono6a0y2GnTFLSkwww+XVPPNYHdF+4tqCfrpSzEl38TSkvnS/ZfU6Uur2OFKlTATnIV2NvftCX0reyJfz5z3+2+c4QGtY8ZD7sgQceaJodhH00GqypiKMqSAvajG9961tGHCA7bi4u81rwAAyxwHSduFyHluX66683AoEGCHLjNCI4G4KwOA+/aFEgHwBtEHEIkBFIDU6u0AxhbsZ51klkTjdaJdKE6DAfHI0PS6Xsu+++ZubmTOK5NwQFL8DO9I77kRYEjDUBmQNOPojLlvjkj6VT2PLOuAbCBeFBw1M7iDuYoHnaMM0O4DHco9A0Im8isyDGGNlxEwF9GPEhg0tJ3UNETcpM9dzLBSg5pw2iVhHd019xJIXnn5VIK242rxW+sU6CWTOkgqmbCrwJoda4VcEZ9Fflqq24tb/XBxtzDejtuo1JZzCAL5WYwNBW8AwQWT2uu7iWRsCSeS9K/r77pZvJx1tvLXVHHC9BLmtan0ygApjG5ctDdQIVxpaVynK3Ep2ykuS9J46XWWGigfPw8NhY0JPjAros8/5dkUJHRrpLbTJ1y1FKdqi5ydo4Hh7rQtI74yyiLLgWj6UsxXmPSbarTcIpW0mlZUKisR8guP4VQZ9+gwXU0dYw1xbygiYGYR7NCOtAQljwnAuJgPighYHIYO6F5gRvrVdffbV56mX+DXNnMAlDM0Q6aEgwYcMRF2mhOUn3V5AmHBuxjAXmZix5gXYIQoPpGvNu+E0cNDis7QdxgZwwbwZzOJ7BeYPl3pjFoekhf8RlbhDH0SrhKZbruBcehlkEHecD7h6kgbaK54PIkQ4OtiBTeO4lDms3kheIDkTMvdPBKKeg2dm0YWJ9Jkd0oPJmosKouw8+aHCD9xQLCglaP7QzerYnUC2Qg2OIDD+aWySYsoX5uYjKRSmtWCGZMqs0W0z9p5H1Av4lF2vwGNSgHFAI7Jsp+N4sq4AHJRYVlDWrpfToIyKlikTjJknjIYdKVNeo5SGWCKKj/xKSxPWUgEDWFIqytNgtE7TcTAqUCA/CBtbDY2hBa5pWMTTto8aqEJgtS7kYyLLF1D5acg+P9QPtO+6jM5gjZ0oSTt9e6qZuJdGyZySa/2/JFBMtxmCBE9LRTqDNQFuBFgVCghYDAoPG44QTTjANCaSB+TAQJOIwf4dlIPbee28jHMzvYakSvPNCFjBpgxjUArIFCYHcEJ+lLSA3EAu0SpjJkR7nIBfki3TcnBocHeFxt1wuG9lhvT88veI0ABJD3skfx0kbgsP9yCfpQV4cceF5OM8x5i3xHiBMECDIDGtKzps3z7Q7ECiIIAQJ8sZzDEaSk8YGkZ1EVHl5i+CB6BHGlSToCy9XfPAhCVHcoaSlQytcp8SVbnSyVngwb0u6Ty1+CLRaR5TOWHmSlhap22sfs/MVbRDbn31O4ucWJE4ty4wUEY8SiABMYpzwGMxIBkSSb873Uv6i37soYaVdgjn/lq4L/iS5f/1LCvu+Rprfdo5kttzWmDBtCwGtHm6mGUxhEvWKqCKPrGyXVVEs+4wdLbPDvHLrV7qs9/Dw2DDEMa6EEVhCmTSzInVNnZKTFnny4ZV6lKEp39h6rB+y2jbTt5eyzFOt0/58qtQd9EaRKdtL4a4rJHj85mrMwQU0IGhdIDHOqRDmXpAKzM8wT8MhAXNX0H5g8obwD1ifkeVTcBqASRxaHNY/fO9732uaEcjL2gBRcJoeNECQLggM93f5IA77EBi0KxAYjmOKBhlhfhCL5v/617+2pU0gaI6EOCICeYGAufUsXZoOpMe9AWZxq1evtjlIECs0OGi00EKx9AnmdJx34NrBjA2as8Mr4ZUxMss2cSGsH4EFurRwdy1dKZX5zxHVw4MCYgIu3ta0Bkl+/ERpGKskprnJaDYlLxPgYS2SstKZvMYv6bHc6hVSuPEqiR+fK50aqeGwo6Xh8EMtSUyZWGcBEZr1F3BskGE+h8egBf0e3wv34Zg0hLpTCgsSLl8kbZfdLE3PzdPy0CHBOe+RylazJKONPqaKQVSysoMDi7K2NflKLMW4Ii8VI/nbc/Pl0bAsH5g6WfauHyuVfEb0v4eHx0bCtOnWp1dk9byKPHjrKlm5uFHK2TY5+2NbaAytYN4bm8d6gEEp0bZam3tt+XNKlVUS6OqQ4oM3S/neSyU/Y5ZkT/96NfbggROHITO/+tWvzBkBi35juvbEE0/YxHzIwRFHHGFODNBsoHn55S9/aaSGdRlxSAAJwvQMDQ9e2TiPhsSRDgd3PwgMwAkA17tF5iEaAE0LxAXTOUgQmhjSYl4O+cLEDs0NeSEtNDB4aEMjxJqKXIuGietxuMBcHszUWKgfTc8nPvEJex7OER+ydv7555sGCQ0R5nSYvGE+BxmCADrNEqZ3jji5MNigedow19M2HUfbOtzGYkuP7XzFyGhZwtY10nHNrdLwxBwOeHioZMtCpbg6pJCoAJtrkXJdXmTKeMnN3lJk9kwpTJ4hOS1X8JWKdrQIwpm4UzofvFfkprsk194t4aytJPOOM1VAblSBV8tclg5ZodeEKhBntCJ7DAzQzkFAGQABdG6uQbEmjx/KdlgLNBm30m+tHWHcXRL521VSeOIBM2EMGydJ5RPvkqx+46yxIi0HmrppASkceoNALyGdBwpd8rfn58tKJT8f33a6bB82SJQLJDsIG1kPj6GCOC7rX1zKZqTYVZG7rlspy57NS1RZJWd8cpY5Esl6suOxHoi1zcdigxbZvLBmitZXFF56XuTm30m49HnJfeJC6/PpNHLalpfpILR8hSzSE1IOtc3fzG26E4eZe4OGBPfTCPxodL73ve+ZdgYTMbyoEVjjBrKA4wFIDU4JMEFDw4NXM5wHQDIgK7iYZg0edw9IAfvuNyTloosuMq9uEBFIBQ4TICqYrvH7m9/8pmmA2GdRfdbuY44Rmh3yAtkBOEr4xS9+YXNxnOvpl156yRYyZ54PxAwtzYc+9CHT2HzmM5+xZ4YgnX322UbUcESABgfzPEjdH//4RyNZpIsZG0SOdCE+gP30djBB87SB6+xoGTRbeyU7Km9qoQykog0gbmSzxS4pPPKYFJ5+uhrZY6QD8yO0fxmtxJlyWaJlyyXT1c0CNjZBva6lSRpPfaPItC2lkq8zQZk1VxjFz2ijmLnyepEFC6QjyErLR/9busZOkQaNxIR1ibRl1EpVUqKdQ3PkMYDQD0ejrXtO22tfpKdl0U5O/7I2Tlbjdam81HDZVbLs/vtllHLfQDu4ygGvlcwxr5VclJXAVpC11IxE2QrqikylYi6qb2hfJde8tFhKUSBf2GkrmaHtUJzPDeiEVw+PoQ/MZrSumalwWR68rUOefbAicaldTvvEDIm10x9od8EeQwTa55e1PYasqLiojXxStuJSl1Ruv0gKD90mzR/9vcqPeBvTthvZUoWCjLb1LBidFDNt/weIXN+vfROajfPOO8+IRVnlFxYAffjhh83ZACZeEANcRWMW9tnPftbm2kAAMINjfsuFF15oC5FyHKKDCRkLgeLBDAKTBsQCDRJmaJAKyBWkAUIFCWI+DlvICeZr5A8zOUgIecPPGKZyrLNDWpiXoSFiXg3EC+0LhAZNEHling5gnSDI2oc//GFzKY2jA7RZnEe7hZe3T33qU0aI8BiHpght089+9jNzwoCZHu8nTXDS+4MFcJ0NIzvVmMyWiPCgFetDVo9VGIXVY7lkdoWHhzZ4WjhgMEALiptsninr8Y5uiV58Udqvv0byHV2Snzld5OCDRGZvL3FY1gavIJ3/fk4aL9GGUStzdoc9JPf610uppVEb0LIEmq7N36ExdYXQY7ODeVO8/owSDwc+ufvsIIMQFWU0aC/W1ipy3z1SueuferF2fjvuJNljj5TShAna4WVtEAVUlBkxDxCtkc3tUsRRQVr1m//++efknlJJJmfy8p0dtpI6PW/apUHYyHp4DBUkmh0qLwNJFWldEshNl86TsDBBDji1TibOxDWInxvnsR5Ae69lydbQs4EwLDb0MLMvO9dI2z8ukYr+Hn3EWVLJj5IszmoyxaR8aRtvi4YTV4nQQACTLjysMS8FDc1tt91mBAR31GwB/U1afIZ0QEjmzp1rmhZntkbgHAQHkoRZGHDXYh4GwSFt5v2gceEa0oK4oDVinwChgewA4jii4eKzJd30Me6LVgrTOIgWcGQLAofbbZwRMFeItGfNmiV33HGHxeXYFVdcYVohCM+5555raXIPPNMxd4jjgPult4MJmqcN1+wkgNgwcp+YrzBK3yNv+kF2jyqYi0MjZ4WFjZYRilDITys3kXQ89LDkHnxEMi8+LaVJo6ThHe+TuEkrO6ZPnZ3S/qNvS1NZK3FuvGTefLp0z54lTSSkjSlrtZQ0sbCn8HlsbmiTqh9Vg8K+At+Zff0myVFtJ/RAqN8wWr5E4nvuonWXYqFbMjvvJY2HHSrx5PHalmRN88M1dr02KiF239btJQ0zpOnZYll+/9RceVo7k9nZvHxj9nSNG+o575HNw2NTELOgqBId0+4EZSm3K9n520vSvWyy7HpkWbbevV6FBt/Be6wPrDew/p49pj3QX5eZ+U0f8cwDEt34WwlP/KDEM3fWQwiRXMHAFaRaL+CaASpvtWJxmkgQMCVLx2HfEQj2XVy2DrW/HSBTOBnAHI10a6/pDek4zCHiOghV+r7kh2MQIpwrQFw45/IJiMezObh003lN54FjBI65d+KOO6T3Bws0TxumI0RmJSQFUhPQ0shvBnUJ9kqSEz74YH+Qg5lngWlamIkkj+hqI/YVKzONu+8uuaMOl+xuu9raOuV//lMyy9bodTkJm0aZC+JQI0ady6Qwb67UF4ta0bTkaXqxdsgVGk8Thn0YiGCEFo0dtgrao9l30UDnRgiVtJY0Tuap56Ry861SnPOoBN1tkt1mV2k48nCpbDFJ0wmTeVu6l7QxXE9rQgtD42q7uh/K4nJBVmkDntOmaxSODKrawyrf8vDw2GgklSiRVbS21cUyYXKjFEpFWbWiS+IKNdTDY93QFj8RmLV5pod2ZCYIVChXAhNM21ZybUuk8PSDEhQ6knZee4DkL1eAwUOsHUFg67ymIdS74I45cIy46TguDfbTQFOESVhaS+Pi1MYF7pgjIe46tEnsuy33I222zBUiTjoPvaW9LqSvST/fUMCGOSioxjTBQn8ot9V//MawDWREX7HteXiYRwsrK/pHC4pWi+RwYE2fjfgH0q1Bm0Y8XXSWpfPXv5Jw1XIJpk6RYI/dJRw/TVb//VJp7FwpEe6FDz5U4iOOsAmNiWcgo9yWrsfmByNwxjd0P9ZGL9C2IKufOSjpt+/skpXPvygND/xLwpeeRs8vlaYWCfbcW7JHHShBtlEiJbJBgAYwgbWb2sCwKVvDrB2JnixrDIxsfvbis/JYe7eM0tbnsPFj5PW4/WRUS+N6AxsPj40H/TutKaIqfbwKB7LkeZFbLl0kdS3dctxp20pT4mXXw+NVAV3BEQ0teVHLUs6ER93RYxVt5KNYBeUrvyOdTz0qTTsfLsEhp0pmVIuWOW3zNSoDmoiSQ0SO9hjkUEK2oWZsiKgZK6yURSYbUzJN2KRQcrBKezw8GJlhZOdlJC2XFZNq2Sko8cmZuVIkJaXKuWeeldIdN0n07HOSaWiSupPOkGjFPGm/43ZpVGm3c4upUv++d1kaeU1PRWttWJN0PTY/0N4w2GH7+jXCqCiZznYp3/ugdD8/T7oXL5FRxcQpRceMKdJ0wEGS3357kYZ6Jb189aRHowQwNmbmDhowZKho2eDL2j30K7fpsW8/+YQsVII0TRnW0ZPGKeGZYCNMCGfejM3DY+NBk1wdhjKzUrTvXSuYt7PE5g4cfOwsmapV18NjXWC+DQ08LXJCeZj6oHvGotHdZCRY8IC0X3a+5DN5yR12qgQ7vUaPai9gHYNeobs44vTw2FRsMNmJzfc0QKzpGae3vy9jvZPzGPZ4uaWitCQl42UybL8ZxddoePnjTC4qiaxZLuVH5kj7Q0+ItK2W7KQxEq5aIXVtnRJlmyR7/JFSbtRmsaKlEH+VXsgdOGjHFZciiVQYKivJqbS3SmHlCsm9tEAaK0k311kXSd1rDpVw772kuMVk0/7kYtbPqWhLQjeYdIr2GbVQGNnp+aaUEjQ/FXm+EMqPn3pSVuaysqOeP2naFrJLS4uRIQS0TOCdo3h4bCx6yE4G82AmYZclKAVy69+WyfIFkey0zwTZ5RCvP/VYH2g/bktOmO7f+vcMC0krg4lYvJYxrmKrVO64RrofvNmWl2g49dMJu4m119CQDGAlqXl4bAo2mOx40CEkr4utvj4L6VfIvrOLTIPj7hoXn32H9L5DelIc29o4Lh2H3tLtDbXn0xPNwLqu7zPEKsRqo4amEGk3jPHCliwiGYWRaQm6lrVJ+dFHpfHhf0lxzQpbS6WM+VpUL7lyRcq5Vtv3GBhAYcvmWUAJDJq8TE7Lf510z5wupamTpHn2DMltvUs19iagUpI/L1kqty1eKoXG0XJQfU7ePGOy1Ic5LTNKtrTOedfTHh6bAq3HDGiqMCrmORPD0VCen9MlD1wdyIQtW2Xf40ZJU0tTop3XOp/0dPQ72hJUfQZnqkc9PF4N6OrL5awEzz4mpVv/IrldDpFwt8NE6pslznVpOdK+xEi3x3BHhMljpmzDmir5STbOVQc8VSbUIwyayiZ45lOZ1pOdDYV7XY4gQGzSr5DjtZPVAHEIjki4eO5adzyN2mt6iwOIQ3qglmilr3f7tengzSN93dru0+fA41rAZHSKMmJzZBPOk1Xz9VdG35ESnMK/HpXcP++XcqFN4jCQwg47aJ9ckfpiLN05fSaGiTwGBrx7/SaZbChBY72EuAYfNUqyW20tmeZmyWgZD8I+6LCU7Pzvc8/LI50FifMNcvy4MfK6iWMkG2SFdZwgyJ7seHhsCrQvegXZoU8JpHVxINed3yYtk1pljyMaZYupYxObU61ujNvzFyRkh5bct8ce6wZrhyKT4LCm+MRtEt19nQR7HCqyy0ESjpmmRaygEbwmcWSAKQ+0JRoCZEFckWsDo7Ihy1Fg7WFtzkZCZVpPdjYG2C/jXxwPF2ngd5zXiZ/0WqRfM/tcj6tBRyx6IxjuGogM+3jYqAXHCfhJx4Xh6NGjq2eSfJKu8wsPersPC03h+92l31ucfoE2dgXtVLNaoEMVms2cV5k883A4V9I+M3PDNVK670Gp69Bn0d+l6VOk/sw36sWFZJJj3KD5TYiex0BAPxrDvLgIzStJrctKmXKUySpxVbFHP03QF/1VuSxfe+YZeUHrQqPk5LQtp8qBjXWaOC6r+f4Q+U1oDT08Rjy0v6EuYX6UIjtRZyCX/L9VUtfSITsfVCdb7zhOqzd1HlrjpBAGqdhPBq48PNaFmPX29D+WAXHnSgl+9xkpVdol2npvqdvmMMlOmC5Rc40s5YvW8ES2wfpyYFQnKAhG7oK9iA2GW3Oz0VCZ1pOdjcEzKnRddNFF8rnPfa56hPnXRbnkkkts5doPfOAD1aMvw71mti7uKaecIk1NTaZV6Y1gOI3LAw88YCv3vvOd7/yPeC69K6+80gjP2Wefbddx/Pbbb5c99tjD3BpyHcfY1qbB6rvvete7bKVf0Fte+gX6SiqZsmlm3GhglCkpiUlWVJaiksof/1CaOjsl0Iax2NIs+eOOkvIeu2p8JT+ouCNWGiayx8AA4ahaZmCj2jAlIpL+pJGi2P8nR99wlCP50BOPSVtDo0zqKsq5O24v2wYqjimTCpUAZRhVHqAF6Dw8hge0stJPoa1llELFDfOKVQ7lwvMWS74+lu33qZNd9h6lVY2x16wE1DtG3/W62CbP0ZZ7eKwbMW48tbeIAu0zooyED18vhYduknjFQsk0jRcZM10yE1iaIA1fuoYjcltuK8HWe0iUa9JfsbUr1vYgG1q7orLrJqh2VD7xZGd9kH5FCHVPPPGEfO1rX5M//elPdmzp0qVy3nnnyZQpU0yLcuqpp8qkSZOMdKCVufbaay0uxIVjAG0KmiFM2UiT1WohTxCXf/zjH7Jo0SKLX64uFHXXXXfJQQcdZNc6nHXWWaYdIv2f/OQnRmqam5tNQ7PrrrvKNddcIzNnzrR7EiZPniwf/ehHLf4999xjcUkfMrXjjjvKqFGjLL8QsJNPPln23HPPHpM88tDXsH5VC3XibjKZkIgq01xSL1sgcs21EnV2ibS3SlculJbTTpfSlrMTJwY2wT00pUJfyNIeGwvUzXRZjMeIuYlORnshrsnYMJbXmwrKxDlPzJGKlu2jsnk5bauZ0hxHUg5U4NIyw+TXTKauGtvDw2OjkFTdqpYmsn4j1Br8h+/NlVw4WSbNzMreh+ekaVxZ+4YGba8Z7KAF9mTHY8MQl7S8hAxSMXCJ44J6yZS1Ha90SqV7pcQrF0u08IVqbI/hjGCr3SWYuq3KDMz8VbmZAWwGvWlSaIusPfJkp1/hXo8zJfvzn/8szz77rNxxxx1y5plnGtlYsWKFPPnkk/LBD35Qtt56a9PAfPvb35YJrAGiWLlypcUBkAYIxu9+9zt505ve1EMwIEmQpaeeekp+/OMfmykc13NProHAYKbGlt8dHR3y9re/3dLkXtttt53lBU1OQ0ODkS9M0wivec1rTGsDiSF/xCdPxxxzjKX5q1/9yggaZAmCdeONN8pxxx0nxx9/fI/WidDn0Gcra7L0kZAcesmyMp5soUs6775DMv+4TfKzd5K2Rx+WuhOPlPrXHqUdKqJzmRcpBS38eGtxwrXH5sfL860Qd5JAw2SNFN+U8tvLHLYNxWoNH3rqCYnLFXnTuAlyDF7dNG0cE3CrMMZk05MdD4+Nh9PJorWhvdc+Tw9Rv//y/56WUuckGTc5I/sc1SATpunpTKDtLwNVXKNxrYugv2Dr4fHqiCJKWUmLT1n/5iVf1HIURBJpf8GQMC07Tos8hj/Kmay5IsA2g2/OXO6oasJmS9zQpmxCw6Lyqyc76wKvBzLi8Je//EXuvfdeue++++SMM84wQnLTTTfJueeeK/vuu69pQj772c8amfjwhz9sBAZiNH/+fCMOaG5I76GHHpLdd9/dyAvXMIJ22GGH2T0uvfRS06xsu+22fKQewsOWuKyQy5yf5cuXy3XXXSfz5s2zey1YsMDIDeZsX//61+V73/ueXHHFFUaoIFaQIK7nHFqlN7/5zZYmJmwcQ/MDfvazn8nOO+9sZMfN4yHvfQ7erRVgGr2KZCrQmEgySiYL114v2Y6VUqlrlqCrINl3vUW6Jm0pDXoN7MgWItV9TCnojD0GBnwB8MovQONUbVb4XtqQbSrma/jSM0+Lsnx5z8xZsu+o0SpcoQ1MchBG2lT2yeQgD4+RCkTM6vwbrdGJXlZbV91cff48WbV4jDSPqcjeh9fL9G3yGjVMtb2uj9R+wjfHHuuBTi0z9ZQ0bcDRH1qXQXuuIcTMQ4Ot1+Mx7IEYiGMqN2xqC8/qMciOWW5YJ7/xDYsnO+uB2tcDofj85z8vq1atMjOvww8/3I4xjwfCAhFBw3LiiSdKXV2d1NfXmzboHe94hzz66KMWSJP5Ovfff7/tQ3K+853vmKbl4IMPNjLU3t4ul19+uZ2HaJD2LbfcYiTqjW98o5x22mlGYiBPEB8I0pIlS4xwAcgRwPwNgrPPPvuYZmfvvfeWq6++Wp577jkjYmh2mH907LHH9szt4d6vfe1rzRTOkRyXXl/CijV/zJQNzZkKxU8/KdEVfzfnA9FRx0nH5VfJmOOOk2D/XZQIKdGLclIxskN3TBra3fZD3jzWD+acVr+dNUb6NRjdhcDyXTBoQVBi8HdTcWtnt/z5hedkUjYn79l6K5kG3Q0DbQiL2jDmJCzrHbP9QMg9PEYKbBRd22CttEkLm5CdSrkgD91UlLkPRRLkW2WHPZtll/3GSa7RWl8utGuM6NhvD4/1QFmJjHJrkwPoLehHlNwg6FZsEFOP+uI0MoAXXtocZDkVJnK46lM5zzyyUTb036b07iojZsIvMzvdY51wAjVanblz5xrRYD4MRANisM0225hGBW0IZId9tCNoRpiPg3ka82qY34OJGvN+iDN27FhLBzO0rbbayrQv3IstZAOzNObTQHo6OzvN3AyChdc14kGCmH/DPJz9999fHnnkEdMiQcDYYl7H/CDM3lpbWy1PkCw0OxAZyBnX7LDDDpZvfrtnZd4R5nX8dsf6EnSp1sxhClXWX0Eolbtvk/iF5yXebleJJm8hlUXzpP7gA6TCXCTi2T8nUNNAKlHqC2naY6PAt0i+CEG/g36LxD9+tXFCDuLnq0HLdvKPlGBHGiC72uhBoigl/2prladWd8jshrzsq6Q8WVkpuTM3sDv2Qxn18BhZoLYptA5anWL0Qg+1rQhl6cIuMyNtaqmXSTPqJVdd3gxTJP7SHru66OGxTpj5o5YW3dBnJI6KtN/APFK36BgTM3Ufhn3QNsa+PuVAAyXA2hJrTzaN6ICvKDY1jREDtC0EzNeYAwPJwYwNQsIEf4gCBGbhwoVmWob3NOJDKKZPny7Tpk0zUzI0L2iFdtttN9PuQGDQ4DCXhjQwScPsjXD33XebRzW0M+eff77FgTw9/vjjdn7OnDkW/+KLLzYvcGhmyNsBBxxg83kIe+21l2mg3va2t5lGCJL297//3TREmMExl6hcLlue3DGe49Zbb+2ZZ9R/sO5RUS3YKugWnnhKNJMSz54tldUrpXGykrIxTVKMlYQx6kit0Lh0xfTDZlTuMWAwwYY/fMjkM1onheEah9ePhyrRMRUf4HtCduy/Ihlfbi10S6QffKKWf2bmuFvSJdJIJt6jPDw8Nh5aj0xDA9gmlTAIsjKKpXVyRQm1HS50BFIqJkNVNhqBRzaDXp9UWg+PdaPKZhBlzSDS+hA6EW3R6UiSAz6MhBBoYdCyALmlWNjhKtHRQ30CkvRYDzhhDOcDEBYIwsSJE80sDDKCxgaTNfYxEXvrW99q12BCxvZTn/qUkRqIBOZtOAX47W9/a+QC7cyXvvQlq+BoetDkoGnZfvvtZZdddjHNEKTpkEMOseMuQFzQNJGnnXbaye5DHNLFFfWsWbOMQBEgXATIElojlzbXkW9+s0+YMWOG5YV8EfoLrK1D38oIfmdW31PnGmksqJh8yHESTRsvuScekXDffSTK1UudlXhG/43mvFxw10+a9hhS4AvrXyWyZS3Tizo6ZHl7p4RBRXaZMKWq1UkA4aUMIXN5eHj0BWhsaVdN4rDK1TxOpGkUImmdrFjeLm2ru2xgI4nLXDkbcrDg4eHhMdjgJcX1ACQCskFgEj9EgGMuYMLG3Bk0NcylQZMCoUgTBZwFQIze9773GbHBZA1ND8QGgvKWt7zF0uU6nAxgpoapGcQIJwiQFMgNZMh5WcPDGu6n2edaAnEgWs6xANol8kE+2Qdog66//nq57LLLjBRh4nbzzTfbPg4NMItDcwV45v6C5UaF1KgcSb2G7rvvlq4tJkhu6+0kXtMmlTUrJW4aZW6HE+9eGqyHxeCpWng92RkGqBWTqvtaZisaVhSK0qFluF4LwaS6bDL4XC0HLNVAsfDw8OgLVAlOTZ3M1YUyelyDVslAykWR9tVUvKQ/iRmLpT6alsfXRg8Pj8EHLymuA45EOLjfjgRg/sWcHUzIIBqQHrQjaHcwA4NorFmzRr7//e+bBzbIC9fjGADt0NNPP409oc2N4RhzZth38dg6Ezrm+vDbBbRGpAEgM4B8nXDCCfLud7/bruE48dJ5xrX1t771LfnRj34kP/jBD4xMffKTnzRCxjG2aIu22GKLfiU7jMpjqxuGeo81qyWaO1fy+u4ydXnJLFwume5uCVtGaR5ySR+a9K2Gl7tiX4SHB6hXCEvVL2sfN/HFs6JUlM5KJKMh/HxuKwfJ17eC4eUrD49NR7VKAYxHrCZWj+XqAmkZm7P6xmJ/bWtKep6KZ7F0T7fVPsjDw8NjsMFLiusBR3AI7nehUDBygtnab37zG/nlL38p//u//ys///nPbZ2an/70p+b1jMVB8ZQ2e/Zs+eIXv2haFTQneEaDHDGXBm3PN77xDSNDTlsE8NzGnJ0777zTzOTWhrTWhi0EBc9seG976aWXjCRBeBwOPfRQ0yBBrAiAayBQbDFjY+4P2iV+u+fua5Cq0jgyLcVnnpLsyuWS22Zrke4ukaUrJFZJN6iv17xX79/zCHSt1Y61f7LmsVnh6hZmilXBib+6wRvLGi3f3bqd3FBvc4E4x//qnyrS+x4eHhsNa1P5YzuKWLK5QJpHBxKHFZs7176mrP1OavTJ6p/G99XQw8NjEMK7nt5A8Lq6u7tNa4MZGb9dALXEALLAOUgIhAOND9oePLBBLgC/3XVs3T73wPEAaWDSBvlIw90X4sXcH+bmEMcdw1kCpAqtE/cmHVCbR7y2YZ7nTN9cvH6HdpYlvKn96xEpXXeTBNqhFj7xUWl+co50X3a1BJOnSf4db9EulPy698N7rnas1WMeQxyuBcpUkl289NhnLsrCckYuWrxEHu3olHOmTpKDR7eYL4LA1u6JpBxkbE2GTKak1/t1djw8Nh09FVL7kuqu1rWVC2O574Y1snxpQZqaQ3n9e8ZqRczpGQYmKlovtU76ZtnDw2OQQWVeP+FhYwBJwcTLERMCBIGQPpYO7hxOA9DyYKrm4M65LYCwQFIgRVzT3Nxsx2tBfBwM4O0NTVH6GI4NcB+N9oa01wZIG0SH69z9NwfoR8OVq0XmPimVrk4Jd9lTwnJJolUrpFLqlHj8uKoFOW4JCFyUjPyjA7CeuKcz9hjy+I9vqaS9VJZ2LRMlLZbjs3krB6yz5M4bvHDl4dFHoE4RaG2r9au6ydeLNDYn50pFiJBWPOqeBmuPPTw8PAYpPNnZQEBCIASOPLh9t3XBEQcXXHy2bg6Ng4uThjtWO99mbahNw2mS3PH0uVq4/G5u0J2WX1wklRdfkOz4Fgl33VnqigUprFgpmVxGckp2kj5Uu1JsxdmzP5s/rx6bAzUCk/4slkrSXWahOZEWJe1xBsPHl78/e1Yk7JeHh8emI6lNiZlatWZpRauri6WhqSKZICOlQkVivIMYfA308PAY3BjRZMc10daml5MtDXwc472sLBUNiNjpfzT0NPxu60JvvwlcUxuvNu6rhXTcl3OR/EvHqw1BqASmem1tfPfb/XPH13Z+Y/9F+h6L+q8SF/X9lvT98m41VLD71vOlspSvvFwyoxql7qwzpLjlFhIuXSrB3Gf02FiR2TNgYpqnULJaVLOaN3SR8DKlf27HY8gD87WyRHxcY7PM1RHpCkJ5oVCQVVp29KxM0t/5cqRlIatxNSoDBypw2Vrv3oTNw6MPQIPK5EgGyqqDZTS1Wsty9VkZt0VeGnUbF7PapCf1lUWhWX8nDrS/7Flzx8PDw2PwQFurkYyqWK5vIdL2PVEY8EqSYOvA6J4PGxtC7Qjz+oZzEqlgWtaOk4B4mkFofWm+CrVKY/baU2TcGI2v55Ytk0x3UbLjx4s0pFdU8Ri20MKSLjcORRWkVpYLUlZyXGeON2pjJMCscYQ3ZB4e/Q5IT0NznYRZ7RuzoZSKDJQxUmhnU8HDw8NjcGFEywhurntZQ1HbaEaTCQjkKlpJpGSnSof8v434x8vN6oaRv1ImNC8+2HmXMUlbtUzK998v4Q5bi2y/ky0cSmGMV62WGLIzboIEDYkDB4/hjWQOlla8an10KERKdiI0PrE06/nANHlsbZOgZ8fDw6NfofWwrjFnntkYeCh3UVnR5Giwektd9PXRw8Nj8GFEkx0E74yym7w21HVxRbJRRQXzkuRUwMpgxhZUktXZfdi4gPmaFOyd8n7zmaLkW5dKdMv10vGrX0v00otSd/JJEo+bbAJsVnvMynMvSDyqQWTGLAnyjcmH8hjWQE7S4qJikhYC1KxVLCuW5PlywbSCUyqRlimNFWgp0Qu4JiHUyb776+Hh0U/IlKV5VFnGTgiV8MSy5CXTxWsoVasffzzZ8fDwGHwY0WSnok8fhyIllczR7CChm7aH9V2UBIURERi18mGjAq5InfCqwmr83BPScfMNInc9oMwmL9l99pYg12AW4kw8ZwnJ7tWrJBg9SglPi1S8s8ARg0RESv4mxCeWdiU3HeXk1yglPMz5Yj+JRUWF7mhMO+DJjodHf4Lals3H0tCiP4KirF5ZbeOB1kGbbueroYeHxyDEiF5np6wBL7YlbaGDqCTZBUskWrBQj8ZS1hNwHdbw8Ng4mGmSIhPFErZ3SfHhuyTT2iZx83jJHfpaCXbZSTKN2nPG+iWY3Krce+VnvySj9Xh04kmSGTVG8jZPw2M4wzQ02gzZzJs4UpILoYnkxtUdctGiBXb+sHydvHnWDMlmc3oOKsQ/BidCMz0NtTZnqkuOenh49D1iespyWeY+UJTH72mTpgnNcvybRmkDX9ST9RKhztc67JtsDw+PwYQMGMlkh4FiNDl4Xct0dciav1wtDc/MlThTku58WYWoWOpKL6+H47FhqIT6XqNQwkpontfyo/OSnTVdwtceKpnJM0VUcC2FKqJiNqhdKbJu++e+KI377i/l44+VWAXcej8nY9jDyI6GjGkBlexoaQj076VLVsu1K5bDluXk5hY5efoUbbTQFmq0AE2gVuA48cwWUodtoVEPD4/+QCRliSuRzJ9TlAdvXy6FKCdnvW+qtuOQnTrtLyOtg0p2qvE9PDw8BgM82WFkWOUlJkAXMhWpj/VIXJGwjBe2wATxXM9aAh4bDLM6ytiIX0XfZSh1KHDMdLAc4oa6qG85p2SoIu1BKE3lisTf+qaEbzxd4h13NPKjRTRJy2P4QpsgqItpdhTQnUDr4g/nzpM5hZLNDzh3+lTZD9NGJUQvmz0mZAfNTtZrdjw8+hX0l9pBSseyQO67aYksXlSRQ0+eKNO2xcRUKyHLBCjMkYiHh4fHIMGIJzseAwwtefChWIpS1v4xv3CptF90qbScfqrEU7ZQkqSCbbUD9RjGqCE7GJiyKO6Xn3pBlirZaWnKyduV7OzS2Fw97+HhsbnBnErqZqkjK/+8fqUsfrZLdj9wrOywf5PNe8UGwganMgxHeHh4eAwOwHW8JOkx4AjiQHK4pF66WIIxo0WlWxV8PUYibORFP36sTVMXTi70SEsuJ/VZv2ioh8eAAk8gGrLKahoac0ZsVq/urFZahq08PDw8Bic82fEYUGQwHayEkinFUnjsUQm2mS3FUaOENfUjr3QcIWDGVmAmpckXz0glCmRppsRkHJmVq5OxOT93zsNjIJFoXjOSCSOZOLVZ4jgrq5eKlLpiyQYMTCTnPTw8PAYbPNnxGDA4KhNnVdjt7JRsa5uEo8dWFx+NxZt+jxDwnQnVAgHxwaytUylvNhvI2DCQOl8YPDwGHIkXxFgam0OtsqGUCjnpbKP6YoYKfD318PAYfPBkx2PAYFYR+q+U0b+trZJr75Ds2DGCc+EQrz6+3xwReFl/l+whNuEOnnWWskpyRmezWiY8PDwGGrh9x3ytsZnGW8lOV0Y6O7Te0ph7ouPh4TFI4cmOx4AB0bYSVcz1dPz0XInauiSYMkXCcqR9Z6h9py+eIwW4gI/DSAku9FdkcRRJQ5CXliCUqQ0NUudNGj08BhQxlVTb5TiTlcbRVmGlXMzIsoVrdL9OYkanvAbWw8NjEMJLkx4DBrpFvK1li0WR1aslwvNawERXJT/aaTrDCI+RAROm2GpoVbJTp8JUA1qd0DdTHh4DD2pmZCbG+AuJ42R53+4Obb9xp6nHvXNXDw+PwQgvRXgMKMwsoqNLSitWCotJRpTIkA7Td5ojDYkb8iSsKRUkG2WkMV8n+ZytrKPBw8Nj4KB1UMlMFFVdxZvmPZaOdm2/C9Ae75HNw8NjcGLEkx3W82A06itf+Yrcd999UqlULPztb3+TP/3pT3ZufcL1118v//u//ytLly6VBQsW/Mf5e+65R/77v/9bSqWSpf/d735XnnrqKSkUCvYbuLj8Jl5XV5fl784775Sf//znUiwWewLnHbq7u+Uvf/mLXHDBBXY954hzww03yIoVKyw995wE9gkcJ3z+85+X+fPn9/x28dKhP8BAvnWPC16UcNl8icY2S9FmZwTWcdKhegx/8JX53mGclUy5bOXtkdZuGVXqkpnZUJr9WkseHgMOG5jSthnXBPzLj26VSlCQthWhtC3XfoLW3JuxeXh4DEKMaCkCgb+jo8PIwdy5c42ocGzlypVy2223yYsvvihPPPGE/Pvf/7bzq1evNmJRG7geUvHss8/a749+9KPy2GOP9RAHAGHJ5/MShtpVaIfw3HPP2b3LVeGus7PTjoNAhTviEZ9jU6ZMMSKWzWbtuNtyHfmFXN17771GcPjNlnzccsstUldXZ2lynABIk8B9CE8//bQ9g/udhstTfyGuRFJesUrKpbI0TN4iWQOf/Nk/T3ZGGihtUP/V7W0SajlozuaSMuHLgofHoEAmoP8QyddTJwOJyjnpbE8G3/ppXMzDw8Njk5BRgXnENk88OgGB/uyzz5Z3vvOdcthhhxlJ+H//7/8ZWWlsbLS4kJLTTz9dTjvtNPudBtejWUF785GPfMT2d911Vzn66KMtfQjE61//enn3u98tJ5xwgh17xzveIe973/tk++23l4aGBvnSl74k3/jGN4xw3XrrrUZAICfct76+3tJ+zWteU72jGNnh+paWFrnmmmvkhz/8oUyaNEmampos/b322kuuvPJK2W677UxDxLNsscUWRsSuvfZaueOOOyxdjj/yyCOyww479JCxMWPGyBve8AZLg7z3F+GJY32+7qLItVdKx/33Ssuxr5PMoa+l+9R/gc3hCEc2Hx8RQINn9UT/ZaKytAahfOmxOdIYBnLS1Kmy15gWqYMGeYcVHh4DBtprgPkapmzXX/SCrFrQLPkwK7seWCfb7IfOp8570fTw8BhUUBk2M6LJDpqV3/72t7J8+XL5xz/+IVtvvbWRnksvvVReeOEF+fSnPy1bbbWVPP/88/KHP/xBTj31VDNXS5uQAQjB4sWLTfMzc+ZMIxG81j333FPOOussIxDvf//75Vvf+pY0NzdLLpeT97znPUZ+dtxxR/njH/8oO+20kxx44IGmEfrJT34iEydOlC233NKIBmm5LWB/1apVRkg49u1vf1t22203IzoQIrZf//rXjdyg2SFd8gWpmjFjhnzzm980AgQBw4zuBz/4gbzlLW+RyZMnW9o8/1FHHWXEzGl6ajU+fQE6z8rylZK54jJpfeFZGfWWcyXYdis9w70IkebHC7jDHY7shHGiy3uxVJHvPDFHpml5PW3aDNmmKQ8N8mXBw2MA4fofUKlEcte1L8lLTzZpvW2SbfYsyJ5HNWotxRqhGsnDw8NjEEDl2pFNdgDakyVLlsgpp5xi2pbRo0fL9OnTjRSgLcFkjDgf//jHTXOC0M9vt4UcsL355pvl6quvlg9/+MMye/Zs6xg43t7eLr///e/NJI55QRAdyBCkCq3Lk08+Kccee6y89a1vNS3LsmXL5NFHHzXTtQceeMDS4R5sCaSHNgjNEaZqkDT20UChoTnooIPMpI24aKLQEq1Zs0aOOeYYuy/Ei3wsWrRIXvva15rJ24UXXijHHXecTJgwwd7J3XffLa973evsmCM55KHvoWTnwUekeOXlEs7cUsJTz5CgMSeVICuZGNtwbMC9gDvcgR5PC6xkyrEUwkBuXbJcLl2+WPZubpE3z5glLYE2UZjOoN3x8PAYGGg1tHk5CjQ78/69Ru6+riRBeaxMmt0qh58+Vs/0nyWAh4eHx8ZA26SRLUk6IsH8HDQd//rXv+SAAw4wjQykBM0IhAPtDqQAMoI52VVXXWUmYmwJzMeB2JAecRw4xlybOXPmGGniPMeIgybo8ccfl5NOOkn+67/+y+ITB43OIYccYsTKpcWWcN111xmhgjhBXND8QJogV5ilPfPMM5Ympm2Yot14441Gdh566CG5/fbb5a677rK5QbvssotpethHs0O+MJdjn/ew8847y7Rp0+zeoL86L337Eq9eIWXmC42fIFGO2RlVcmV/PUYC3LdGr4POdKmSeMpcs9aHHOvujOjhGA+PwQfm7YwZ1yRxpmyDFYVuSJBvtT08PAYnRvywOZqUBx980MzL9t57byMGV1xxhfzoRz+Sl156yTQuHDvvvPPkd7/7nXktQxtDYF4PmhVM3iAfaEEgEA4QFNJn7osjDGhjIEfEf+Mb3yjHH3+83duRIAfIyjnnnCNve9vbjNBgpnbwwQfLZz7zGTNf4xqXJiQNbQwaH/J6//33GykjMPcH5wqcf/jhh+3+aHUgVZAcCBbppLcQPZ4TjRBxCP2DjETLlkiQz0lmwgSJTYvkx+9HGvjeroRBdlaWi3asJZeXrJ5J/nl4eAw8qJmJg4KWMXklPayJVpJCQWuuKX18TfXw8Bh8GPFzdpiwf+aZZ8r5559vzgeYpA8ZcZ7N0mZczH058cQTTQsCKcCZwde+9jUzHeMYTgYgHG9/+9vtGuBe7xe/+EUzV8OdNeZyv/zlL+W9732vzdnhnpAmTOfw6IYDAUdkSBfTMzzCoXFJfy60P5Arl1ccIuBJDq3Tr3/9a5uv84tf/MLick8IFum+6U1vMjfZkBoAoWKOD/cHaIl4BxC9bbbZpocI9TUq+ijF739Zsk3jJfuG0ySaPFHZdyBRRt97zGRXb8Y2IsDcLRWSQi0Qc/Wb//7Z52RFsSJvn72N7N1AORCth1k/MuPhMZDQ9toNO+A8Jihl5Na/tsuCFzsk19Alp793S8lktbb6NtvDw2MQQeVXb8Z26KGHmuYF0gCpwGQNwgAxQNAnzJo1y7yktba22jUQC7YESACECMLCnBdMzDiORmfevHk9cXBqALH5whe+YPdz93fAgxumZmhvPvvZz1o8CBJOEvDwBoniN4TKBUgKXtRwNIDzAXDkkUeaORoOFXieNBxhQbuD0wXcX6OVIm/km2P8Zg4TWibip/O4oShpx9iNkYO+LynH5lK4JGUjOZGGoKiksaskhRmTpNDcqAQHP2x6vJIYNPl1dkYOWHMpzoTS3l2U7rgiZSU3Y/MioZWBvifaHh4eGw/077F2L6PG5W1trGypTrQ5t/bbw2N9gGyxNvmC42lLFwd3Tfpatk5mQdZATksjHdfByXAmmyhcHBcv/RsLF2TC9DVsMfnnXi6fLr4D+8iNDEanwXGuYSC7t2esRW26tXDnSY/3UOtAy4F7IRsim6YtkEYKRjTZwWsZWp1Ro0b1aDkQ8Nln8j7aEEzJMDeDqFBYKCQUcryhQXLQuPz0pz81bcz+++9vzgUodLivxusZFQUQl3THjh1r+05j5ADxwDkC2hi2xCOMHz/efqNdGTdu3CsC82re/OY32z4VkDTR9rB4KXnlWdKExVVsiA2LlGKqR6DCQo5wyEDAjA9HCJCl2nxuCGxeOYKq/qdjDDQfWd3Bxhs6I4VuKWieGiZPlpD1gGKEWm/GNjKhnYh++K5iSbo1UFIbq2TdlwcPj8GBpIVW0Fbr/3HjA6lECHOhlNn4yuqxgXDCOoOwCOp4tUXGwjpl4cKFPXOJCWly4AR8zPJZhgMTfmSZ3/zmN69YwxAg+5AOJv5ONuIcx1h8PQ13DUBW+tjHPmYDyxwnuGuZQ43nXJdHd577OkKEwyqmSbjj3JvAc/K8kChkRuZ1c9zlk7guTcA7cVMSGJBGXsRzL9MpOMe1PDNWRUxBwEII2ZR0uQ7CRVo40sILMFMc+O2Ckw2HM0a8NzYKFUI9pAH3y3hI+973vmcFkXkzFGwKEvN3cCQAyeE3BAPHADgxwGU1r5G4FCK0NLizxmyN+TaAuTaf+9znjLTgOe2CCy7o8ZpGgCjhphpCRDoA5wiMDFDJL7nkEks3Da6jkFKYMcPDrA5TNkAFpDLgoACihuka2ifAda5icS/OYcbGc3CMPNaSHJenDYHexjo/mid2s5G+I5VoY2VBcVySjFbcrvselMZjj5TypC0kzCSandDWc8hIFLBet+89hzu0NFhh6dJvfe28+XJtxxrpCkL5zfY7SJ2Wnoyt2a7l0RcFD48BhrbNJjEk66C1LijLDZfMl7gwVg4/u0kmTMsmddXDYx1wsg8yB0I5A67OZB75hH20EFjMEI/jyGr/8z//Y4PAOFz685//bGkh62CFw8A1RABZBiLBMaxjIAnIZljPMBiMbIe1DPOwGdz9xCc+Yekg93Cc85AnBoVxWoU1zmWXXWbkhXUNSW/33XeXp556ygbDOQfJQF4jfeRECAdTApApcSZF3J/97Gcmm9100012P/bf9a532cA7xIVlSHhGyAnyGkQG0od8x0A4z8VyKVgesS4kMiIOqSBMeAxmKgbef1lO5OSTT7b53OSJ5+M48ZAReTYshZBFnQXQpgxsD3Zo2fHGtVQiwHwYKhWFCG9lEI8PfOADNmLAmji4YYbYMM+GygYxwmvatttua9dTEQmQFgoPBRzy4Y5TSNMkgkJJJWTOECFNRhyoUJAVPLrts88+1aOvBI0CeWa+DRXUERgqG9eiFWLtHae5ApwnL9yP4zy70x5xrC+IDoj1Ml5vqAGtjr1pjrGnlbm8ZJHI5CkizaP1Hsl3MHsm22f0xEu3IwV8cchOa6ksFeqMClV56wg1+HLg4TEoEdZlpKE5J+WKNund+sfXVY8NgBt4hdRAHhggRhjHcRNr/TFYzLIZyF+cw8kSGg+AFgcTfqxzkM1YPgS5DXmH+cY4nMKyhoHrv/3tb+adFhkJsgA5gUjgTRcLGSxx8HT7q1/9ykgHGh3IFySFdEmTAWyuQz5CM4NchLwF2UAehGi5AXDkMeRDBsUZbGZ6AuchPBzDyRQD7Nyb45Ab5xCKvGNRxOA6eec+yJTIeUxXYJ888Bv5jX0nszmyyDkC7xX5jmPIkWiozjjjDHu/DJ7jFRjUynzDESOe7DhNCoQGkoMZGBUGMzZGBSAzMH0KCA4K0poXBwofgeMUGhgzhMgtCkpgQVIKqiM07HOe9CFGjoykCx3OEEjnQx/6kOWvN1C4qVxUehYmJR+AvHMd5IzjLs8uP2lA6BgpScPFq427IXAanYxpSGPlMGhrtFOUskTt7VJ8Yb5kJ20hUX2D3oc4RnHsmp4DHiMD+tE7taFfo2QHI8ec/g2cZp0CYYXCw8NjoEDL3FMNbSeWXL32ZY2hCn0ihc6KxNiienisB9xAM0AeglAwZ5plMZCN2EIG3G/I0NSpU03mAVyPbOMWVEdO4zdrFHIM4oFcBSFh+gEDxmg4mOcMiYDgIC9xDPkKDQ0EgXTRwHANchueb9mHnCCfcd7JRewTyBdxIBOQIoiFM6tDw8MaiBALjmHRg0YJYoUjKPZZyB0NDMSH59xjjz3sWXguwDNACstV0zwC+xxn34HfgHxC5iBlvDscY0EYIV4c5x2gdUIDhFYsncZwxYgnOw4I+1Q4Kofbd6BCoPlw7p4pSI7cpMmA++3m27jfBNJc23UgfcztMwrBCAGLnHLvWhCHNKmgVHBGGNy15J/rGEVwbJ/g4H4TJk+ebCQsfaxPoPWHeTs90P2ybipasTLMZVqyQrLjxkopk1RevBZU30D17/CvgB4UC7R4Ih1RWVpprONAmiiD9vn1XB8VRw8Pjz6Cad+15qrc2dCS0/pbka72kujGw2O94OQMZC6EcMy00KZgboW3WubeoIVhiQ9MtDAfw9oGWQzBn+uxfkFYh2hgzk9gDg/zVdDOEA84GQ45CVmMqQHEO+GEE4xgMWCMrIQchOzERH/20X5897vfle985zumBcJaJz0w7YgHZmkMOCNLQVLQRqHZQQ5Es8LgOffBIRYEDrM4iAz7xIeYcV9HVly+SdvJZLwfZ3ZGID55ZN/B5YljzO1hi9YIM0FM2CA3TKdgKRXIH8+8YsWK6tXDG57sePQbbPwFDgOZoXNU5oOWp6GzS4p3/lMyWqGjqVvo8dAqqNZo7UMpkomA68nOyABdHsVjYUe7LNfPH8ahTI+VoIexNd4BvMcTHg+PgUdPk6w7CFXZWCZMGSVhXSxrlpWklFgYeXisF2jfEeQZ2MXrLYL4V77yFfn2t79tjgEgMa973euM9Jx++ulGDCAbkAGIAQSGQBqQB9Jh8BeS4dYv5ByT95kPwwT+Cy+80OSNc889V/bbb7+eedUQIOKSp2984xtGErgn3nEJeNclbZemIybsY6HDYDNedCFaDDQzUA0h4RwEC80Qx9CqQO6IB1HDQQK/0er0Bubl4OSAxe///ve/29wg8sI8buYtoR2qBaZ+WCpB7tDgOMKGhRLviGkT73//+y2/LJ0yEuDJjke/Au6C6RpzdkoqsEKA4heWSOdLCyW/xXg9gRSLJzkmodOB8juwdVc81RlB0M/e2t0t3frVcWIxSslOHCWjW3Qpnux4eAw8Xm6TtYXWOomg19zE0guhFDqzUuz2rbbH+gPSgudX5sugbUDz8OMf/9i2aHcoX5ACtDwcQ2jHRAxARiAILJAOCWHONZoPSA7EA/LjiBGkgzlAn/zkJ027wm/AFAJM2NAakR5wmhPIDMcgDhAhfpMexxxJY0v6kDHywTniff/73zfzOOb/sKYhZAnPtzwrJnQ4HCA+GiC0KziIcnN2aoF5H5qgI444wub6YNYHMYS4QFTQILnryBPgNwFzOIgepAbHCXjbxZQOJ1zMC2KahJtaMdwxdMlOTZngpws9SB/0YUBCZDvMwkhM2OJKUSpPPEErJ9lZM62xCK2CWs9pGy5h4zEyQAnhi3eUilJUCQqlfEs2ayQnQbUweXh4DBJgeorAJ1LfqIJEriLdHSqAFhCytLYSqLOu6pow5gewPF4JJ5yzhSSUy2UjDBACCAZb5r1w3JELyAde1XCjzHwXSBHzZJiXAinCAxnLgTAn55lnnrG5MpAUTMzQdqB1gaBABtAcMb8HMzbmt5AHzP4deSBdPLKxruGee+7ZQ5KI44gOgGQxN4ct98BpAusjYqbGXCD2IVWQKEzvMCvDtI30cEiAMwKuTb8PB+7BOyF/zqU2wb0fjrv8EjedBoQPZ1U4JOA+mNphTkee0OywvArPPBIwdF1Pk+uXy8MrGlEzJ1awcCVxLJr+GaJPOmTBMqLlTEUZdSxhlJNMxxqpXHuVFB75t9QffaxkDj5QguzIGFXwWDtMc6N186faWdxTiaSlUJJ3TN9C9ho32kzaMri6sAbcK6I9PAYKSffJDDsEPK2LsQqocSSdq2O556ZVsuqFQPY9oVG23Kk+qa+ZqGqWDLSW62/tCfR665E9PP4DCOuQCIR65tTgvQztB8cc2XEgLnNlMPPCIRMCPII7c3ww1dp1113NPAygOYEwQDAgSmgzPv/5zxtpgWRwHWZiF198sZnPMT/my1/+srmaxnQOcgGZwXEBmhp+X3755aZ1whwOBwUQnJNOOsk0L5Ak0sYjLiQJUzvuQVponcg712Bahyc3SAtrALEkCaZ15BXRnOt/8YtfGOFivhDPhStq3gX5wzscGi2cM0CsyAvaG0zWnMturuN9Egft0V//+lczDfy///s/I0C8E9JzJGk4Qp9tCLuervku/LSQIjRRXLFQiVjICc8V2Hn6sLlCUI4lh5xaCaSi36Xw7znSNfc5KW0zS4JddtH+0hMdD+oslTaW7nLJFhbFDfmExuakiuspTqeqtYeHx4Ci2ttmEtITZjPS2MRoeEY6O0pS0XY/GcLw8NgwIJyjuYEMoLFAE1I7Hs9vHAhANq688kojEhAMBzQ3zz//vDk7QMMDEOTxQsZ6iW1tbT3CPa6ZH3/8cSMveEPjno5YEZyba4DDA2fyRf4gEGzJD44M8GrLPZgj4xb+RLPC/Zhnw5o6mJCRPnN4SN+RN3c/0ocMYYpH4Dd55l5cf/3119sxnhky5a7lmdFSufcFKcL5AsQNjRb5c++IPEPmcM2NZox3MBIwdMlOb0jXCf3gQYz7Wg26RaCy3z5stkDxwt00HtmC9lYp33G/ks9AGg7cWypjm/RsogL28EAL21WJbHAi1DAmn1NxyuiOVuuqcOXh4TFwoH+1PtbVRWpmRsJcIE0tCdnpaCtKuaj1OGLWpaKn2uqOnvfweDVALiAoOAhAQ8GEfkc+HNCQQCRYJBRNBk4HmNdCHMzVMAljyQ3Wx2GODMI/12CuxrIieEdzJmuYeDEPCC0JE/6Zw8McGogGhAH30My1YR4RC5geeeSR5lSA5UXQqkBaSAcyg4YEV9XMrWFODYQEt89uDpAjM46QEJwGBwLCs6NlYg1GtESYnvE8OCPA4QKmdhAh5u3wXtDQYLKHKdw3v/lNc+oAASL/kDfAcziN1te+9jXzdAdxIj3uASGC+IwEDF0zthq4xzABSQtfUQtz5utfT45pIRsmjzmkUMiWJKfkJijhDlE7xWMPl2jf/UVyDZJFBRdqZ5l52W2ixwiF1s0OLQ6fmzNHFmuZ2Ku5RT46Y6YEWkYwg1HRyeqwdnnVCzw8PDY7rAt1/ajWxQyCWs7q74KnC/KPv3XJ6KmdctBxE6VpbKQkqF7rLUJGNb45NaAW+3rs0TuQ0xDUEf4hOQj764M0GQI98mBV9oPcsA8ZcNoY9tnymwAJ4Zi7hkBe2AJHWiA3HCd/Lj5w8Rxq85SGi+vuC0iXQJoO3MeRozTpc3l2z+RIE++LeBAnjru0iUccwDHiOHCOa18tv0Md+myZYUN2gHsUGlcrOFddroWlwgk7rk+cbKsYXmqtwYco0G5Nv0OYqZfSuHFSf8hrpC2sM6G1qYwgq98l78nOiIcWg5VaFj7/xBPSGZXl0EkT5W2TttDqqieU7FB7qbrDtyn28BgqoE6ypUJWyY6SmKXzy3LLn9ulbnRBDnvdBBk9Sdv3LGRHt3YNva0nOx4eHpsfw5fs2A8Vts3/VxWc8m3sZkecKetrz0klDiUbFyh0UtQQoOnRb5IJ12/kxmMYQ8vB4qgiX3j6aYk6OuW0bbeRo1taJLRKi2aHxspXXw+PgQX10W2UwmjbHmu7LnFZ1iwVueb3qyTXGMlhJ4yTCbM0UljnyY6Hh8eAA64zdJUb1XbXIWl/E3WcQ6TiUk/IpPZ92EyhJOWMUk7m71RiiVHHRrGZttHpVTzR8TDEUqrguS+QOi0n43N1WnZAIhR50cjDY7CA/rVaI2NbNc3+5fIMTZQlqmSlrY0jCrNf0zB8xlM9PDyGKIauZodcp6Sg9EO4w+Z6GnCgJr5H/8N89eh7pxu00Xn+6e9YvwNet4A3YhtZSNdTh0iboCfa2uVrCxfJDlEk/73NbJmcZUJnaKamNjIMUO94eHgMDJyokNHWXPdjyWooWYMeFbJyyU8XSqnYINvulpHXHNkk2fqqtyiN5WouV/l5moMd9NbpcXB6cr6gBjpvB9eY2yGsaPQa0+ApUtE8hi6ST6x/beCC9RLR5PJx3bGhoS8Z2pqdmsrETxccWJzfgttn68NmC+htQvsoGX3/SnTY1xNs6e58l+cByloe2stl7S5jaajLSbM2S2Ecvdyv+pFhD49BAGvMNSDoVHWv1q5r+66NeQ63vHEo3R1adyusp0O91fh2WbLfM3DhMYjhGl4H990BXvZwGVOWCDNGDVFMSAatWHfJh2EUrFfGoUNvnnOHVl1GJvXw8PDYLEh3o64LpRltK5a0t6xIc12dZGHD+t8aJ93GxpI9PDwGBWz0Pqmj/DE/iXoom4f4xNLVVZSohCDUmzDk6/KgR1p7Y9DfHCNAcPR3pN+cnxEklo+Pto52OlCiGzA3S2mtD0M+BNRtC6FkbH4eZSDSQK89tMjOsHJQ4OHhMfhAA6NNZILa1kZPLI0juWLBS3JHW7ucusU0ObZllORCbUzjrFToR/Ua0wL2JOLh4bG5YcbIKi6YKQv7WjFZN03/SFSJ5OZLWmXFS1pJs2vksBOnyeRt0fhgyob5CxW/SpI8BjdcG23auFg/uX4zczSk39JWfW6VOGqUciljayohANc26x7DBPp5qbNBGEuuUfvhbFG/d0PyzSkKQ6Q6Y8bmyY6Hh0e/ggbG2sR0S6PNjh0PMjKvUpKLFyyQZzs65U0zZsn+9Q2SzSrZiRKyQ0Sz/h8iDauHx3AE5iwq5Wo1xEA5Gd2NquvssNTDP69slUXPssZdmxx09DTZaq+M1u8asmOV3lfkQQ1rp/VP1VQxITul5Ltrg1ypdErropy8+PRqWTCvTX9n9fvTUDPyr1u7jpF//52HOviKaO2ax1ZkzwPGy6Tp+k1jzFUhO8y/Gxrf2JMdDw+PfofJN26nB4wKa2MZBPJ0oVv+sHCBdHcV5eytZsku+byNJEF2rA/VXa/Z8fAYWLyS7ChUABYlO4gQ/HvgxlZ5fk5BCoWK7LbfeNn1sIwEmbwKGgi/1cpvwrCvyIMaiIQpwhLHLL6p353PpucWPhPLnLvWyMqVnZK3thoqC9GhXGgkJcEZKys03h5DGcyn5cPXtxRkz31HybRt6jlgIdYygonbUIAnOx4eHv0OGhgTb1ItDcIRFhG0Pg+2rpFfL1wou4T1ctrMaTIlF2g/mYwS2nUKLx95eAwstMbqHwScxMsawrDVY6unkTz54Gr5991dUmxrkZbJJTnp3LFJ3KqGAA0P6/Ko2FH97TEogbeBQImskR0lsxFtMYSmLOVCWS759XLZcrus7L73BGkei9BL3LwG/a42l6Ns8auzLj2GNPRbMidL622gW6u6Zt4I+L5Doy7DdXxp9PDw2OyItNVEVKpEkXQWi1LSznFMvk7qlORYP6kwksQfDa559fDwGEC8gqggPiDcWk2V+oas5HKJYNTVwRwPjyEJ+3AQWkwUEXBxQlGSQL/r0hdDGTO2QbbfbZS0jIHI4pQi2SbXUSaydgwX4z4M9ZDTz8oWDR8fmPrNN2afuj90QK49PDw8Nh9oJ6sKZRYT7ezqMqv+RiU7uUCbJOs0ExHKsxwPj0GGav10O3hgQxxuaKqXfF1OgiArpWJkVdfbjQxFoMHTb4v3LfvGKtQG3RKXY3nq0TaZvXWzjJ+sx3Eiw5c3wtOpoTspCyYkY/ZW8mGIBxZ/T7ztaUUOWEuJCk3ZoFwMLfrgyY6Hh0f/QvvOSowpCw2ldpBRIgiVpCyturOiiOVvJOPyWamLyyYgZWzV2ShxUJC2+ffw8BggUCcB9dGFvB5NhOKGUWXJ1Wv9ViEpMBvVUCoqJDGQYTarNgGPazwGNwo2is93s7F7vltUL8sWFGXZkrLM2DEvYVivwnBgcjBiZCbToKEuOcYhM1/M+zDEA18z+QeB5Zvax1Ww0/NjSMCTHQ8Pj34GI7/JXxsQ0qBNp+SjWNrKZXmxvU35TCzj63O2xo41sDZa6JpU/nl4eAwkknoIsVGxwSpmqlbq7ugxzTJqbIuE+bKUyzgvYNSC+RsMVFTjJtKxx6AGJmxAiSlzcIKydKwM5N7b2iViLbSxHNfvaW10NVirXRWNe475f0P+3yu+sVV6+28h+TNk4FseDw+P/ocKOUZ0HFT+CeJAunS3DflJD9RnlQKlBaMe9LSuHh4egwKIDtjxpzSuWkWbWxokE5YkYO4dc5tNk+Pi6DYV3WOwoioWmnki3yyQJQsLsnJZUaZMb0rOeXgMMXiy4+Hh0a9wNMWJPSbvsBBhHMqqclnatRUK9HdDmAhQDlVxKvnh4eEx6MCI78uIpXm0kpygW8IwK8WuqrDMGaJZ1HR8j8EJ/UZGdNhkpFIMZenCDv0Vy4QpEFwbnfLwGFLwZMfDw6N/Qd+ZbBKLfSY7RhUpa+c5r6NdVmkrlNeTY0OM2zCh0ANE/v/tnQeAXVW1v9et02fSeyAhEHqR3lGawEMEBFREFEQRUVHsFQvv7wPbE0QUH3YRRap0pSi9dwgQCAnpbTJ95pZz/+tb5+7JzZDQMpNMJuuDndP2Offcc+auvX5nrb2PEb981CWP4ww+Vqa5MF+S0RNKkqnplEy6RlqWJPWnzqhc4ddLpfKsM4gpW9yyqFk4uyivPB/J8JFp2XrHOhWu/WONiQryMtqAva/pLRb2r5xf3XH60nfbmupUHrtYLPauKxToV7ryGKG8GSrr5/N5O24ofZf5HKZO/+Bix3GcAUYbAv2/so0sqXfUoytbcjkplJKSSaZU8MSOEx6RNivUMifKHSTH2TBIV4tU1zFkcUI62sL7VsKP33/IGwKxmQ7GOpJFC9ol35OQ0WOaJFWld5F+WP0E9r5S8ASCeMDhRwRUEsRCEAKhLsdiPm5DXp9wjFBWR+VxkowSqrAuxUM5nb6Zz3k9OA7HDWVNy07/4FfScZwBRZuT2M0ptynWtqQS0qkz7T099v6GbCotaTa85qnh6hsix3HWNfwW44cQa/pdJlXnNA5rkGIhIe2t3Vo9OITsRxfn1zq2zmAjvr+Y41IpKW3L81Is5WTshLTeYB5Erf7ev1WCWGCK4Fid6MHhT6fDgAkxYT+EQF/BA2sSL31pbW216RuJFs5r4cKFdtyOjg6ZOXPmaj+DdW9UAgi4rq4uOx7T9vZ2mTdvnrz66qvS2dnZu455p39I6A3on79cx3Gc1VBi2Gl7wssEc0PcJimPdLfL32a8LIuztbJFTUa+NXm8tmA0qDyD0cYhobV0v8iGvVRjZUdwHGf9EP92Y/g19v1F4qzmZNaTKbn7Hytk9KQ2OejYKZKuZ6QC/U2X9LfN+zt4WaUzaCmViKQgQLToLb3y4iUybERJDjhytGQa9f4n0mq9194aBwGAYHnppZfk7rvvlve9733S2NjYG9G49tpr5Y477pBPfOITsvXWW/cKEwTI448/Ltddd5186lOfkt/+9rd2jBB14ZiZTEaeeuopufPOO2XFihUmbjhuEFUXX3yxzJ49W8455xypra21dew7bNgwW54/f76Jje7ubrnyyivl+OOPl2eeeUZuuOEG+dKXviQNDQ0yZswYq8t+Z5xxhh3j9fjc5z4n06dPl8cee8zOvaenx9ZzTq+88oqdN9sDXJ8f/OAHNs9nBHc9XAfnzaHXK+Fix3GcAaWoFibJEKa0kzZ0LS5RUf7V2i3Xzpwpkk3J9g2NcubksRIlGcA0ToMpJvOSLiV1N91Hbbubd8cZ7BRk0Ssi/7pyntTU5uTw47aQmpHq1Jrvyi+4R/+tYsEZpJRK6oCXqtQEFyXKRXLFhc2y6VYiux7ShM6RdDKjzuPaJwUF15NpLpeTj33sY/LBD35QDjjgAHn22WdNrBDpuOmmm2TvvfeWrbbaysTK+PHjZfjw4RYV+dnPfmZCiOgPgoESBA3lW9/6llxyySVyxRVXyP333y9jx441QYFYaGtrs4jNFltsYXURSsuXL5fDDz9cdt99d/nRj35ky4ivF198UbbccktZvHixzJkzR3baaSfbh/N9xzveYfsSmeG4lS51WGZKfcQR36ulpUVmzJghzc3Nto10vf/85z8mfg477LDe+nzPvfbay5Yr6bvsvD56vXzQe8dxBpZglq0J0H/ipiAhLd2dUlBxk1LDXZ+lI3P8noZyhVX3cxxng6CuLqlCJyXFQkba23mKzi84/Ord5RjsmA3W+4XPnutWm5yMZNjwOhURKV23qjPfH+C4Z7NZOfrooy1Kggi5/vrr5fLLL5d77rlHRowYIS+//LLcfPPNJnyef/55eeGFF2z+9NNPNwGDiJg4caJMmjSpt7BcXV1t4mbWrFkmqPbcc08riJlDDjlETj75ZJtHTCEqli5dKnPnzjWhgSChLtEmhNZxxx0nBx10kH3WCSecYAKLaBHH55qEzwyfP3ny5FWmm2yyiX1P6hI9Yvrcc8/J008/bWXJkiWybNkyix7xHYlKuajpP9zyOI4zoCS1bYwTB2K0GdV/E7Ksq1PyacSOSL0Z9VAcx9lQqanVUq+uRVQtrSu6dQ2//mAB3OUY/Kig0f94gWh3VyTJVEGGj44fRjGkeH864BwLp59UsXe9612yzz77WDQDMbHrrruauDjxxBNNcBx77LFyzDHHyDbbbGMRlieeeEJGjRplURdS2h544AF5+OGHTUDQ3wURAiEatMsuu1iK2OjRo62MHDnSCp83depU2W233WSHHXYwcRUEGFGf7bff3gQV02nTpln62s4772yCBahLlGnBggVWSH+rLER8wpRIEue2aNGiVY5PdIhz4ZhEkDbffHPZdtttLQpE/x3El7N2uOVxHGfAodkJ5prhCnpU77zU1iI92ZQ0JFMySY26PTCMdZCV/sgLdxxn3RHpjzhZJTJuclYKuXpZOK+dlXQOjn/bcT6bM4jRO6j/EINLSfPigowYk5L6kQkpmAFnFDJuZP+AE4/QIV3tK1/5ikVgSAmjfw4RlN/85jfywx/+0FLKKPRrQaggZBAxiAfWE2VBtLDPn//8Z4uKEMmhDtGij3/845YmV1dXJ01NTSYqmPL5f/3rX+WRRx6x8/niF79oggoBRmTnvPPOsz5BIYrEuZB+duqpp1o0BsHC+SJgiAhxfpzz//t//8/qkT53yimnWNSG9DfOF2FE2hqi6qGHHpKrr77azpVz/MIXviC33Xab3HjjjSbq+E7A93DWDr+CjuMMMLSScXJETEmW5QrShZxJJKROG4vh2mjE5qhC4GiDu8qy4ziDGktTSyakabj+nqOU9HQmpKtDpBjFT/D7z012BgwEqZrdUlGks60ow0ZUS6Za75ze13h7/9lk7H9VVZVsttlmUlNTY38jwbFH0Hz5y1+WH//4xyY6zj///N4R1BAp7AtEP8aNG2fpYiFVrDISwjFZRpQQPeGziNAgOC644AJLPSNqRN8cjkl9Pru+vt4EyPe+9z2LODFQwEc/+lGZMmWK/Pd//7dFX+hjw3GI/BCJIkrDubC844472vlwfqwnGsQ6BNmECRNsQAVGdiPahHC68MILbbAEoj0IJKJNnGcYPCEQvrfz1nCx4zjOgIKDE/fGUSOt/2N0lnR1S06nKW1Y67QRHVGVte3JRErrx/VieRTPO44z+AmDiQwfWatOYyS57kg6WukQzoMNtQSudgY/mFy9V/lcQtpbImkaUSWZrFpl8pH7mUpREiDKgeAgfYv0MwQK4oFIDJEZqIx0cAyiJQiPMOIagiAcm5SxX/ziF/KrX/1KLrroIhuF7dJLL5Vzzz3XBgjg+Cyz/ec//7n87W9/s2gT0SKEGCIMIcQyU84BIYSo4lwRO8DnMc+5sA/7BjifviKFlDnEE/sREWIf+gV95CMfsfP8wx/+YMcK+67uGM6bx8WO4zgDi1qZVAnpkoxfuxGV5MnWJZYW0VgoydiaahmZzdAimC8UaUOrVdQxwjy5cXecDYX419opw8fy2+2WttYeWbKgU6ICnbjz/nPeUNB71dFSkKULe2T46KwkU4idKH4Q1Y+piEGYMMXpZ+ABUrlIAaNPDmIngONPCltw+KlPtAaR869//ctEylVXXSXbbbedRUTC4AREUkhFY9S2M88804aIPu2002xgAqI8RFFYR5rapz/9aesvdPvtt5sYQYRwXPjHP/5hAyUQiWHwBCJCpKdxrogcBBr1H330URvQoG9EBhi2mlHXqEsfI4bFRkRxLkz//ve/yzXXXGP9lxBW3/jGN8p7OmuLix3HcQYce6jb+2AwIa2FvDVwGRVBDbynAJnTq21i0eM4zoaIChv9LZekoA5pSXKMUcDDDuvr4WpnsGP9q/Tu5bqK0tWRl6pqXuqJTY47/PcnOP0UhAvvwqH/DP1UEDGIiFAHEDsMDgAhysEy4uRDH/qQCRiiIkcddZQJnMooSPgcShi4oBI+P5wHUyIu9N1hkADqI0RYx/FZ5lwYovrDH/6wDXxAlId+O7fccotFoBhwoPLzAwygwIAKvFT04IMPNlHGSHAc+53vfKd9HoKO/j+ks5111lnlPZ21xcWO4zgDS1EbyoQ6QBRrt0qyNEpJJpGS+mJOmmqqtSldaYqYs6VyW+HukeNsIOjv2zq46482kg6RQlp6OlJSyOEs844tkledwUykTnpJbXZ3u0i+J5JMnd7URFpSpZTeWRUK/WiQK0UIQoO+MWeffbbceuutli6GKODFnkROGNEMIQAhIsRAA7yXJkRRWMc+CBLS4EIaGOIJwcKUbXweKW9so9CvhsJ2CtEX3uFz2WWX2VDYRIuoB4gb5uljwxDZiDT44x//aAMdILbokwMci3MPkB5Hnx6mDKvNwAx8B86ZdaTF0fcISLcLgs9Ze/yloo7jDCh0dJVUAT9IF3j7dklOfeIZydZWy7TuTjl+hx1kCtscx9mwifQnnuAN/Gn56wWzJOpslBHjI9nloAYZNi6rDmePOoqvTe9xBg95dQkL7QV57I52eXVWjxx35hhJptXRJzonOO7pfhM8wf1kisOP4EBgIHCIosyePVsefPBBW6ZPy0knnWT1SSejg/+hhx5qy5UglNgPoUE6Ge/PAT6D8pe//MWEEH11DjzwQIvEhPMIgob9iRpRWIdQqiREdxixjVHV7rrrLku5Y9joIKqA70Q0h/Q8xBzDW1MHkQO8f4cR2RiggGgUgxgwAAKpeUCEh4EQnLVD72HCxY7jOANKyRyggrWPJQYg0EbzlCeflkxtRvbUtcduPl1G9lPj6TjOeqTsTjC57tfzpH1pvTSM7laxUy/jptRJMpGTBGNTO4OWqFSUzuaS3Htjs7SuiOTYT5ESxhZ67KgxVxveH2qn0vVkPggNHP1KgREiMaxDDCEagCl1wn4BBEaow3aiQAGOQ6SFKev7iphAOEblIAOVsD/bORbH4Bw5t3CelVMIn0mdcL58Bulv7Mt2BFKIWEHld3DWDr2miZV/BY7jOANBomSpLTwXJG2/W215KpuWXKFHRtbViT/ndZyhQuygFaOS1DbgKKZEf+bS1VaQBKOTJOMn3s7ghYTDQk6ks70k2Sq125U5xUZ8j/uDIAaCg88yTn8QKaxnGgqEKdvCfn1Z07bK41Vu7zuPKAlCJ5xjJdThHKlTKVLCNByPZfavXAaWETphvnJ9qMvxQ4TIWXviK+w4jjNg0FioAS/RjJakU5eSKW0EtEWlv07Na9sSx3E2SHCEGU0xkoamrDp6RenpYfjpghTJgOrHkbycgaGkQrWrXaSQT0p1Dc52/w9MEAhOfoBlhAZOfhABOP2sq4xwBEG0OqiLkKCsTiz0PV4QF30hshLOoW+dsByEEMerrMM+4bvxOZwLo8NVHi+IIM6R7ZXHqDyW0z+45XEcZ0Axs41x1wlDSs/tydOiyrhUVibVN+rKgWtMHcdZh+iPHf8vmU7J+E2rpbo+J6VCWpYuSNgLKsvWwBnEkD21ZL6K1K68jB1XrfKV/7DeuIv9F2modOxDeSPebL1KKo/fd9/K5crtTPsKpbA91IG+Qqjv9sr5vgQxVEnYP+z3evs7bw0XO47jDDgmdOzfkjR3d4vkizIimZF6dYok0X9pEY7jrEfK78biv7rGkoqeHp1LSVd7SXI95UFKnEENfSw7O4oqenJSW19eacOG24wWdxudDQ//q3UcZ8CJZU5cVnR2SqkYychMtVSz0V0gxxkalFNV+U3rz1uqa0smfHo6StLT6Q81NgSKxZJ0tuckk01KFWlsZp7j9EQreo8dZ0PDxY7jOAOLto+pUqRtZEKao6LMa++WRCIvOzRkpUkdoXwyU67oOM6GDGMQJBKRJPU3X90oMmZajRSSCcl1pWTpnB5LiHIGA9wHOlFRVr0n+RVJWbKwTRpH1Unt8Kw6iXE0hyREkzulkuRVEOWjkhRLBYlKel+t5LUUtbBO77RW9rLuCumjvfN6S62U18d9izbu354PPe04zoCCiaEUSwmZ3dkmV81dLC8X2uWLW2wm07INEqkz1H+Z4I7jrC9KOFTmXTEKVV5efjYv99/SJYl8QiZvnpe9jxsh6UQ8CpWzPsHxpcRph3GJWTKzIDdeuUAmb9Ykux/UoIKHF0LnpVSskrTa6igqmCPNi2KjQkLX6zFQtyHVLXiUHgBab1TX0+9H74vdg/iGJOz+bJzxjQS42HEcZyAhUz9VjCSvYuex5qVyw6Kl0qJrv73tdjIiUiGUTIm2oY7jbOCY2FEPK1HUH3SyR+a9HMl9N3dKT0skTaN75IjTRuhv3QebX/9wnwDDW2l8S/LKYzm5/YZlstVOiJ1qSZJrnFDBKtWqZ5LStrQkS2Z3yfxXO6W9JSmRiqBIcupQFnR33Mnw6MoHnlln6C0kXZSrz93c59haaWxsKN9aFzsudhzHGXBy2hRmtR1sVWN746LF8p/m5bLtsBFy2oRxks3npZTJuthxnCFAHNnRH7O9U6dHOluy8vAdy2Te8wVJJlNy/Nk1kkqHXu/Oumd1IgcXcKUbePdfu2XO3BWyy35jZfouRSkl07o5KYmoJAtn5+WOfyyWUeMTsumUYdIwIqP3M6eHymqdTHyYhIocig8zvl5Qt15GTEpKitc7EIIrr6NsrKB1XOw4jjOgFLWBTeW0oSwV5arFS+SR9hY5bNwEOXpYk6TyKoWyVeLviHacDZ8gduKnzD1S6K6SJ+5dLC89Hkm+Ky0f+HK9pLPxsCTO+qBC7CBKzf+NxU7sCibk5l91S1tuiex5yESZvCWrVLRo3Y7lCbnrhmZpGpmUrXatkqYR1ZJMF3R7XithweOITkktfuxXe3LyeqMsNBE7QeRs7GLHpbfjOANKghc3KN3Foqwo5CWnjeqYqkzcFCbj0LvjOEOE2HdWkpJSH7i+gRdA4nglJSr4YCTrn1WdXkROEDqU9raciphIaupYLDvNqmmee7RVFi8oyfZ71svwMdWS0luZSGDFszqjU5xpKym9/ayPj+dl3ZdwK8J7gDZmoRNwseM4zoDC8AM8ROwoFqRVxU5Bzc7odErXawOb9Kd/jjNUMFcr+FXq9OID1zdVSzqTsJ96vtMfbQwOwk3ifvAwSqcYaZ0wklpVtWhBtLApIXNf7pGXZ3RL04ik1I/M6+6M4hb65ARhQ+14qPH4ERZ1vKyf4vTFxY7jOAOLtoNt2h7O6miT5nxOSqWMTKWTTkEbWfWMUjw2dBxnCGDusf6uGWQ6IVGyIMNH18iwEVVSlY1k8TzvtD5oML2DDdZ7pnY4op+VlqKKl5Fjs1LbqKJFhc5LT3fJPbcskrr6SI48sUn3ITqHEEqatDE4hNaNiy5H6lqWCOd5WS8lCFinFxc7juMMKJjcrihSoZOXQjGSKmsmFUtvS+h8ucF0HGfoUFJXWH/8RAkaR6hznCzK0nk4waRNxXaBPj66FBbK/9jMoGZl6tfK+bD8Zqjcp3LfyvmBgCPb0W2mvGQRnXI0xj5fpKY+I8mMzmuNuTPbpFgoyfTth0uqWmupkLXIjokkrWCFedZTKtd5WS/FeQ0udhzHGVAwvW0qbOZHKnKitAwv5dTwZEXSKbqy6lZPZXOcoUWynNyUklRVQqpGFKWYKciKV/OxM2//I3WI9PR1zga3s/Z6wqS/hEp/Hee1YG9XpSTp+IojVPR2pJJ5qa5NWTpbIa/3bFFKmobVy5gpui5FLKegJaMlfkwVF1xJ7nh8162fiG33sj5K7Nq/9l5vzLjYcRxnQCFJbUVXp8zpaJN8WmRiKq3rcHLUIVIRFDFMqeM4Q4BKB6s8nyzJ+EkNMmxYlSxb0SpzX+7SlUUpRd2SsJQbXO1K535wuyWhs3dUHnhldaKnkrA9lGKxaPtWrgv1AgPVoTxOM9PPQdgovR+pM4lkQVpWFKWqJpJx44ZLOhVJ6zK138Ue2XX/RmkYpveF0b3ER9NzNjxc7DiOM6DQnrZ090iHTqNkQkZXV0splYwj7trmxi8idBxnSICfbr56cNhLUtcgUtsQuxsL53aaYx/RV48Uqkp4L8hKn3/QUSlOGOlq4cKFsmTJklXESaVoqSQInGeffVZmzJghHR0d0tnZKS+99JI0Nzevcb+BocLm6scyRHGpVJTO9h7J1hWkui4hUSEpLUuK0jgyJfUj4vNP2uhsfe6Z42wAuNhxHGdAYdy1JV1dwkvVaWRH1VRLGueA4hbIcYYYOO3BcedHX5R0dVHqmrAEKVm+OG8POexFwmYTVk5VSvTuOZjB8b/22mvlK1/5ivz2t7+15VyOwVfWfPaFQsHqffvb35bzzz9fXnjhBZkzZ4787Gc/kwcffLA34rNuId1MKZ92Z3u3pGpzUlUnkutOypIFBZk8tU5q6kXS6dhY+8MpZ0PEXyrqOP0IPycKT/oqf1prSksI9fsS9ufpYSU0iGHs/ErWdPzBQFEb8HOenSHzSgkZV5OSkyZMkG2r66Sg3k5KG07G/4lH+HEcZ8MGR1htkf7WrSO7JNWB79FpUVYsqJZ//rlFElU9st/ho2TcNDbHQ9DH9os5kl7TsQM+SLjhhhvknHPOkTFjxkhXV9cqgoTIDOeezWZVDKR7bT/CZ7PNNjMh9Lvf/U6uvvpqq59KpSwaBMOHDzdbTlSnrq5Oamtre4995ZVXSk1Njc33K9bU6GeU7w3vPorR5UJCHrx9oSRrk7LL7mNkznM5uff2Zjnq1LFS36Q2uncfvT/9cIP4rlwvROCLL75o15BrtmLFCnn11VdtO9cntI9MJ0+eLCNGjLDr+8QTT9j6PfbYY5X2j+OFfdifa84yx2Mb62bPni3f/OY35VOf+pTss88+1q4CdTkWdYD17e3tctFFF8nnPvc5ue++++TSSy+VX/3qV3bPQj14/PHHy3NrZvPNN7f9enp6pLW1tfdz4S9/+Yv9fX3sYx+z8+U8KOPGjSvXcN4ueh0TLnYcp5+o/Ckxn8/nrQGsNIgYL4wuU6De6/0EK/fFUGMcMcjBKAcq5wcbuVJezn76JemOSrLNsGp5n4qdTZNZKaboSkkDiuAhd99xnA0b/T2r0FGLZGIndqbjBxq59pRceXGrrs/JTvvUyNa71YpkiCzQj6RsD63/HgJo8EAE52tf+5qMHj2613GGSjteac+7u7vNmZ02bZr86U9/kl/84hfyxz/+UTKZjDQ0NEhLiwo+rY/TCwimqqoq2848jvzdd99t4mfgwO7q+Zp4Ucda5/IdCbnrxnkyebs62WRyozx9T7u8+Fy7HH/GRElXaX29b9zXqFQVR+XWEq4f8PmzZs0yQXHKKafYut///vd2rWfOnCkTtL1A+HHNjj/+eNlxxx3tOhEZoz3cZZddrJ1kO20ux6oUSltttZUsW7bMRCWwjm0IUUTVN77xDduXwmeOHDnS7g3bEDq0u//4xz/kyCOPtM+89dZbTfhwTuPHj7f7xPE++9nP2vFfjzPPPFOmT58uTz75pFx33XUmboBzQoDxfbbYYovedp7jfv/737c6zttH762LHcfpLyp/SjRY5HIvXrxYttxyy15jTQlGHjBqlctAnTCtFDU8VSLtAeO/33772bpAqDMY6Y665PSn5wjPKfcZWSeHTxgno4rqNKT0mtkwmTS5PiKb42z4qC3rFTs8YS8/xCgVJBEl5C8/adeFgkzZOpI9DholiRrGY0TcxPYrtgdhaXBAlIXIDk4wzio2u9JGY/crhc/1118vTz/9tD3Fv+yyy0zsIHoQP+973/vkxz/+sbUHH/jAB0zkXHHFFbLvvvua046T/8wzz8j9998/QGIntFGcayxGVebYUvvSjPz7+ldlt/9qkFppkPtualZnv1uO/uQkoauOSgnbs5hI94sc5bqFNpPpj370I2sr3/3ud8vSpUulurpavvOd78jJJ58sm2yyibWFXBPEx1NPPSXPP/+8XXOuM3WnTJli4uF//ud/rC4PGmkvuQeXX3653HvvvTJ27Fi7fwhLIiuLFi2STTfd1I6DsEAQHXHEEbLXXnvJD3/4Q1m+fLnU19eb6EKk0KZzTAQXnHjiifKOd7zDPo/1bwRRGu453w/hhPAFvtO///1vE8l8PteDc0Ic923rnbeOXksXO46zNvDzId/6gQceMAOKgQKePN14443WCXXPPfc0Qxm2YVQxeO9617vMEFMvbAOMMXUwwp/+9KfNQBO+//KXvyz/+te/LOz+85//3PYJRrFy/3WKWg8MSPnBbDzogE55Px1bVNrJK/ke+drMV2WyNpgnjh0n2zU1SJqXzmnlohYbLHN9nb/jOP3IqmKn/ERDLUGP2qhIrvplm+TaEpKtz8veh4yXsVvo+lLW6rOX9dhJIIAGT1orTjKpbAganOn58+fbemwvdjo8rGIZpxtnHUecp/6nnXZab2Rnp512Mhv+4Q9/2JzYr3/96xZBOO+88+TYY4+VQw891Jz7//znP/Lwww+bY1/pnvWPjSdNUI+DyMFYc68SKmL0K8ydkZH7/rVIjjmjQZ6/PytP3b9cpm1XLbseXqf3SOWN3deiDTKT1P/WFr4b166trc2iZzj5tH2/+c1vTAQQIZs7d66lD/LduWak/n3wgx+0CA6CEpExceJE6wNFVIg2k30RjtT56Ec/ahGcP/zhD3YMrnMYDIJ9wzkgPkeNGmXt6tSpU61tPvfcc02c7rzzznLJJZfIGWecIY8++qilJV588cUmqnbffXcTI5w3bT7H42+i8r5VwjnwN8K5Ecnhb4nz4Bxuu+02+85cB+pxDMTRtttuayl+lfTP38LGg14vFzuOszbw88EQ/vKXvzQjxpMZDBfGqFCIc4cxZhhAYD3zGPCf/OQncsstt1hDSrgcQ4dBRwjxVIrGkhzmYGAJt5PegHgKYidQOb9Oob1kUv54EztaCuWZVKkoD+UiueCVl2WzVEJOmbCpTK2u0uuiDUJKGxq9Pvbs10b5cRxnwwbHH2OAwEHs6K8bA5FgmOmiXH/ZMmmbXy3JTEK226NGttkbUYMjx4MR3Q93xFLZBo/YwTbjkGPXefgUxA7LFB5yAbYeu33NNdf0Rg8aGxvlwgsvtIdaiBceWiGEqIeTzpR0KaJGw4YNs+gAn3XXXXe9JrLTPzaea4sgTZdtNlddxY6ufu7hSB67e4W874zh8uCteZnz4grZ9Z2NsvludZJUe82DK+5PyfpZrT1cOyAL4p577rGCOEGsICoRfdttt52NXkfa1/vf/367frSJXIvHHnvMrhEC5+yzz7YoC9vZH4HCcRFA9IVZsGCBLSOQOC73invElGMQ5fnEJz5h94B2HEgfQ8xsvfXWFt3j89mfh5Of//zn5aqrrjJhu//++1uaGwX4HI5LO46ooYR7yRQhRVod6XZAHy7afgQNvgLtPsIJIcy+fAeiV+H+M11v7f0Gil4vFzuOszbw80HoID54CsMTpWCI+v60WM86phg9jCvLt99+uzWGPMXiaR9PAIFt//znP+Vvf/ubGdhvfetbcuedd64S2QlUzq9T9CsGoWOUvzP/qnWx5WvbO+U6dRC2qa+WE8dOkgnaVDL0dPxk0bq8amUXO46z4VMWO2oU4siOOtURv2+iB3m559ZWefUp3a4O85RtS7LXESO1Pr99rcOeGBOzJ5VGZf2BQ84DrEKhYOWRRx4xRxSwuTip2GdSz3iIhe0mksM2Cg5siOzgyCJucIYhiCQcWtZTH5vPMg+1gtMd2gzK2sP9QbSkVhU7+v/D/+6Spx9eIcd9fKLcdtVyMg9l94MaZOwWVWajbSAZ7meSfdYevlcQPIgbRqlDTBJhYWju7373uyYyiMSQ4kY62Ve/+lW7btyLhx56SJqamiyt+4tf/KJ85CMfMaGwOrET+utwL4NwJZpDOhmRH9pthAvXPERaiMKRho4QReAiThk8AaGCwOIciPbQHnMc6rCO9hwBQxSJdDseZnL+iGYEEA86w7kgmEiRO+CAA+xvh8/Hn+DvBuEH1Gd95f3vn7+FjQe9Xu5hOM7aEgw2ecUnnXSSHHPMMfLe975XjjvuOAuDh8J6DCBThiwlPQ3jjFEmN5h58o4RQjwRxMjRgGIkaRh4EoUhHkyGDheFZ7gJGuTYXzE4w/iVGUl5SRuITCGSMZlqqU6xJbJhqO0Fd721HccZElTYARYwV/TLkURKJk1ptGUpZaVluTrPpLP21seO6sbYCx8UYGtxrnFSedJO3xrSzSiHHHKI9c/hIdU222xjzvoFF1xgjin1w5P6IFaISFAHONbHP/5xixBg548++mhLi6JOEFfsB/1r78vHsntAITolkutJSE+XSFE/t725JMuXdUnTiCppHEHcncqqfBiNzc4lbu/6A9o3vh9tHuIGQcF7h3jod+CBB5qgQQgyahqigHaS60LhOnGNaX8pQTz2heOTMUFhkAmuMZEShMxPf/pTu3f0n2Ibdbg3iFjEEGKGdDZS1Ug35J6x7w9+8AOb0nZTEETbb7+9DYZAdIj2m4hQ6CNEXySiVKSkkYqHoCNaxd8Pwom/IY7PwAcIOMQaIo5z4m+pf/8GNk48suM4awE/H/J3GUmGJzwYvVdeecWMF0aKaA91MIh0buSpIMaMpz0Yap5oHXbYYTbFWNM4UgcDT8dMDCX5xvTVIbJDegOdJwdLZCevJVMiNQK0Ydf/ItLXiiUpaEM2R7/LeS/OkrF1NfLBCZNkem1a5U+k/kxGkmZ69LzdjjvOEIEnHPyg+V3n1fbxPDUMPkJfnITcdnmzLJjDg5usvP+sOklmiBtgO/JqE9S5NnswOIwC6U084Q/vwQnpyNh0bC42OzjbRGSw32E78zjTRBbog8PDMB50BUHEAzGcfPqrEFnYYYcdLJLBMMz03aHjO2lZwGf1i403by+IFgXbrfdokd6P+29rlSgfSXU2Iy2t3bLLASNk2o58rooIvZfsEScd939kB3GHs4/AoZ8r15KHfKSqkUrG4A4IHwQDgwNwbUntRqSEe0R0B6ES+uzQ5hId+d///V+LvnHvuId8JvtzT6hLWhmwjs/loSORpeeee04mTZpkQ12HAQqI4NDXhntDHYTqUUcdZW0ybTYCivcmIYSIKiFmfv3rX9uU8+F78jn83TB0NhEfxA/nizDiHIk88TdAuh3RJlL0YH218UMBvXYe2XGctSU0fBjRT37yk3LCCSeY0aUQwTnrrLPsiSBPiqjDdgwe8zzFwrjvtttulnP8oQ99yAwhhpOGkHowuA2dPSKMZ7UZtDm9JnmdmbliBY/vZFgmLaP1eyV1XVG/C9NV93McZ0jQa6pwlONFK7ZQlMmb1kmh2CaJUpV0d+BsxzZg5b90oh8cYH+JBPDUHiebaSg8pceGY68ZLpin8QiWysJDLAY4wMl9+eWXrZ8m++DQ/vnPf7b+njjI9N3E2cfJBd7jQv8Q9qN+/8LdCKIUStLVGUlne480NlVL67KCVNXkZNgohA19dbR9s1RD2iL2Y5+1h3YzRHa4TiE6wkNDRqgjygKIiptuuslECIIRoUg6GSOpMY+AofDwEIjKIJRoV1nPfrTBn/nMZyxyQmEZgUFUhegahaGjQ98fBik4/PDD7R4TqWHKg0vEFuILgYIw43yJ4gQRTPoahQhVZdtNoc4dd9xho6pyT+lHRCSIbA7+Hkh/Y9Q45hE+RJGoE/Z31g4XO46zlmC0Axhjws9MacTIvSYaQ2OGEX7nO99pucVAHjFj7WMYGXQA48s2Ijs8TeI4wWAOdmg3w1UIz/14g8CsjnbL8R5blZEGrI0aed66YZWZJGz8Jcdxhhz84LVgDmKTYIyekJRMdWRprp2t+usn+mNGAFvHTH87928fovM8nPrSl75k0QOmYZ5IAuD4kmZVuZ2HXExxZnGKDz74YDnooIMsHYq2gXnaAqZ77723Od1MqUt6HC/KJIVpYBxdjsd1piQkKpYk15mQ7q6cNA1LqR5VWz1cpH4Y/Sq1rvWt5B5xPxE+/QdtJ4KOtpIoFg/46J+KcCFaQvvHNSRbgutG31YiJCyTKYHQDBEThA/Q1tIPh35SiIW+8JmVbXaAdeFaE5UhCkdEiePzoJJR9HgYybkhSMjIIHJEu42QQWDdfPPNlrkR+t0GODYCh2gSA1QwTz8d7jFThjTn74HvijhDMCGyeXjq9A+exuY4awE/H3KN6WjIkz2eOIUGihA5y4DRplHEmGMYETNf+MIX5O9//7s1bjy5IrUNQ8kTKVLYMKSE6jHcpLHxxufBlsZGAlsqykmRt8yVMubeIF8Saszv7+iSP85/RbrUwnxz2tayWZotDF2akXRRG9JUnP5m+fyO4wwBECqU4Bwr9uZ9fuv6my+lpNATyRN3dcqzDzfLdrvUyvb7jpR0TSSR2rAUveJJZeuPt1b2E0QHArxigNHWiLxj20lvI9WJVCmccZzYYItpG3jAha0mYkNqM20CMFQy0X4iGqQ4fe973zNnHftPO8HLM4lw8MALQgSkXzCPL35BKHS0FOWRO4syf0677LzrcHnm3g7Z4ZCCbLL9MCno/apOhsiOClS11TYqWz8kBQXXk9QxRAxOP4KHVDEEAdcFEUMkhrpEelgm/evSSy814cFwzWRHcJ24zqSbMYDArrvuaiKFOoySxv4U7iX9gZgnwnL66adbWxvg/nGtifAQyeGcEDxEb7jn7Mc5cGzEFPeUfrrcZ+7pqaeeaqOzhX42DFBA1IhoEAMsUB9hQ3oefztEmIj8IYIQb2R4EGEiNY/37iD8SINz1g69F4nUd0gOdRznbUOeNcOHYqgJuWOoeMpDQ4bBo2AkWeaJEI0k4ofx9BFIGFNSJFjPqD482eH9DIT1GXb68ccfN4NMmJuhSfmcMBZ/oHJ+XUJzlVQHhdS0uCGMYfrUsuXyaK7TBM4xYyZIrTo99OfhBaIW/bERDUJD6jjOhk/8my5bBlbo7zwIIKwCTntRil0JWTivyyIHoydWSXWd2g+dT5oTTh8RnQwicICx4djfv/71rzYc8rx582wbfTkQJ2zHrmOLqY8Tj2NMlIfIBRF7HN7//u//tvQnogXUx6lmns73OOoIIpxunGYc/NCG9K+NX5kq2NmWkxee6pRUokqaRmSlc5nI1rvXSqZeNyZSKkDLNtruI/ePffvvARXfi+tChgORGua5fly797znPSYieTiIgOA60YYiCHlIyHXiWvLuHdLN2D8MEIA4oQ0lxTBcO6a0w0RUSFMj4sZxA6EegxYgNklnIx2d8wmFe8Y+DEDAZ3P/SFE88sgjLcpD5Ccch/OmbechJ/P076E/D+fFQ0vacgQYQpfIHtEdzp9jUI9USPZz1o7vKh7ZcZy1AENFuJsnNozQQxpaMHT8tAh9Y7gYhe2//uu/zFAz5DQNGU+CgmEkmsMyER6EDk+IODaDE/CStVtvvdXes8O7CDCSdHJlv/BZYbquoX9rIZmXdJQWXjaXV2GT0X+bS1Xy95fmyD3Fdkmqc/O7zbZTZ6YopbQ2m/ZC0bjh1Jn4ia4dzXGcDZsKd6JUtkn2UCOmxLqoW1oWJ+TumxdJZ2u97P3uWpk4PaPVLcFVy+ASO5UuElEE+tPg3OL0kn5GXxCcVur1tcPYcN7PgnOOI0tneB5mVdpu9kMYES0gEnD11VdbZILRPCuP1y82vtStRa+12l5e/MwgMUvmRHLXjYulrrZKxoyrlwXtz8sRR20fB+aSkdrv2E4jkCxqX7bbrw/X7I1dy1Cj77VjmWsXxGMlURQPMoCYoQ5QLz4nPSIHLe/D9rRtW/lZxSIj3cUClgLlPVdh1U9dFfuI8hQYxS6VDuewKnwXzpnPtHOxcwtHiKNJcUQpFsk8CFx5Llzv1zuTNZCgv5UT0L8hf8+O47xdMFCIEYQHT5K+9rWvWc41T+douDBcRGBITUDAEFInZE0hvxtDTD3S4AhZ8ySLp4R/+tOfeg09TwTJO+apIGKICBJ534z4An0bgnWOapZCUg0971+w/yJJ6XW5sbVNbly8UL9fSaao7/K1LbY2ZwZDn9BWNEqWdB9MedzouthxnI0De+9OVJBXZ+TUye6RYWO7ZN/DRkntCBy+qtjhW89mbU0EJxzbD0wrn+QHqMe6MMW2M4+DzvLq6gPHQ/iE/if9TtnbY+Q7ouyl7qw882CzzHikRyZOHi7LV8yV3Q8bJ2PH15k1TyTj9EM73yBe7SDlA62RQXoDNxb6/H1t7Ojfr4/G5jhrA2lmQKiZsfRp1HgyhzChhMYthMLJ064cSpJ0CNLTaOzYn348zFOXRvX++++Xc845x/KMSZtAACGeAtQNDeV6QW1qbES0YdTTCM/J5nd0Sgs53vodp6azUuQcy/Y3flJFTTc/jrOxYYOSJPNSPzJjPnNHc0ralkWSSsRPve1lw4MYbDDpUpTVCR0I64J9ph2g/urqVsJ2UqQGzKbbYbHFiLWiFHIi7S3xYBFSSEiuuySjxtTqdoQOdRXqVp6OPbR6o8JneFlvxXkN7m04ztuEhonIDWPtk3ZAegINGqlqiBTGySf/mE6HDFkJNGLUAfZHBJGHzOg7iCDye+Mnm/HTPzpeku/LMdmPYSrDewEGAzzso/m2l4pai1iSSM9/WVdOG9CEFFIl2X74CLM01Fj5dDAQ7+M4zsZBbCnSUteQVlsXSb67RubP7paiOttq8nSbOsuDmCBE3kiQYL+DLafu69UP9v6Njtk/cH3NaktXRyTtKxKSzWSlu6soPd0JSWWI6QSo1/ecWA4Pq9ZU2G91672sm+L0xdPYHGct4Odz5513WidFho0E3oxMoaEj4kNqGrndPN0D9qFhAyJBjK2PWGKoyVAnNHwMT41wYvACRA8j/9ApMoz2sr4x41EqqiHRc0nEDXpOje23n31BFieKUqO67sebbSkZy2cuSUoFEP8V1R7HaWz6n+6XdAPtOBsFBbUXyVJSGHjtul8vk86WGmkcs1ze9d7xUjta12ud1AZiD4ItZwqrs8lhWyVrst3heAOG2dyC2lyubySLZkZy780tUp2ulkQyLUuWL5SPfJX+R+V2CGFEX8tS3B+FMysleJV0/E4bZ3BS+Rf0en+bGwv63b3PjuOsDZU/n7iTYTxqD2BcVmdoKufZHvYLVG4Htvdd13d5fcHXS5QiKejpF3S+WsurPUX52qsvybDmNjlhh21l/2xGCqmMGeAkwkib2yiRRhvZvKU9eK8dx9koiOyt/fp7V7vx1D3LZMZj3ZLrysiYSSKHfmiY1lDHe3CYtyFHiWtvkCYt8thtLTLrmUhqqpPS3NIuU6aPlP3fV60VV94ABpbBUvNAy5oz2+Q3aDATfj+VvsNg8RnWB/rdXew4ztvl7f50Ko1OOAZT1lduC1R+zuq2r1dUpzDwQE5Pi8Ywqaf6eEubnL9oruygDeJpm20u49JaLckIQEHs8L6GtI3CxmhA8dNDFzuOszFQafOWzOmSh/+9VFYsrFf90yUfOnuibUsMovfsDC0K6gDHI34VipH88y8LpWNptVRXVUlb93LZdb/RMn23Gq1XbnPCbeCe8X8JkcSobDlri8K9HHTt0kaGXf2K+5FMxcNpV96Xjfke6Xd3seM4a8Nb+fmsydisLnIDYR2fwXyYDipUpxT0lHj2R2JDeymSW+bPl6uaW+SQ0SPlA6NGS3WaVrI8FGYCscPIRFl7Nw9iJ+lix3E2IkiLIuU1LYlCJA/fuVReeip+E/6Hzh4jqazbg4GjKFFRxY5lsRXkyovnS9RdY/2laofnZL//Gi0jJqolt07uvE9HK1oKG8tkISSku0MFE+9+tXuoq1fXJL35ZtHpT8r3o37EynT4wKDzHdYh+t1d7DiO8/YpqvWg301CG9GiLtzf2il/XLxEtkkX5ZjJm8om6bQkU2Wh4ziOY49GMBw40T1S7EnLvf9cLq++UC1bbJuXXQ4YIYmq4JbwIEjFT0hz5aGPOeDm0zlvkSIRGaLqqlaiXEL+9rPlkk1mTVu+451VMnUH3Z5u0JpcXbXrpYQsnFWURbN7ZNGreVm2qE1qslUimfjlmuZAr86D3Igd6/VBEDIhJX6vY0WGD2+y28DtUU+/fEs2zvviYsdxnLXChixVZ6RQysnSQkpumLtA7utqlaNHj5V3jhgh1amkZLzhcxynF8ROLFgsNKwzC19OyJ3XL5dMdrnsd/A0Gb05NoPIAQ61Ch6EkZkRc93YohN3Xd4qJa59pNdU59uWRHL979p1Li8jxmVl94MbZPiEDr3mtXZ9S4WSNC8qyL03t0tbS06qqpMyalxGJk5NSVV9ScUOo+lxpEr7Hu4J0bnyrLNO4HLHvw6RMZMb7d6EZX4rCB773W2EuNhxHGftKPIunZIUokgezhXkqldmyYpit5y12VaydSYruUxKalzsOI7TCzlQcbQ3RIUL3Ul5+M42mfNct0yclpYd31UntXUZtS1aN5Etp7oy6iPv5lEnjmiPm5W3jnp7UZSXZCkrsx4rygN3tKj26ZEt31Er2+0xTDI1BUkm8tLTmZXZM3Iy65l26WzvkUlT62Xc1CoZNrpGahtLkkwjRMuFg67iRbKAoHXWFaGJNW9e59MJ+l3F8/H9CJEdFzuO4zhvmYKaj2SpIHN6EvL7ma/IC6kumZRMyPe33FbtbEJS2uglPf/ecZxAKa8FIaOOtwkYOsz36EJG/vzDpZJK1kjTuJzs+s56GTOpSopJoj84aZH+m9P6eG28q8ztylsljqn1SMeSlNx82QIpFKtk8lbVstN+Gamq49UA1fLvv5Rk4eJlkq7Ny+bb18v2ezfY5TdfWUlIh5ayM22sxoW0FMWwh7POQNEgQE3ZIEZJAw2bmNl4xc7G+c0dx+kXaOYiFTP3tbfLony31OqKCfV1klb/hO6tupF/HcdxyqhNqDQL5fe2JKKkjJ/CSI1FWbG4KDMe7pHWpSVbTwYOfXWKpWqJSlVS0nX2GNvLWypc25KKypdmtEhnZ1Gq6yOZsFmkU70FxbQseElk0aIVUt2gYnO/kbL9Ho2xf2yOMo+vmDKAgS2WCQsVZTWrvKyDAjrldq3sp8N8ZYWNE4/sOI7z9omKMluFzc9mPCvLUmkZowb2sLGj5aDGkZJLJiSj1sWHkXUcp5e4o5863nhkPBLBEU+bK7Z0dkHuuaVZulYkJErmZOpWdbLnEXVSsugOqW9aiwco1v/AeauQ/te6KCG3XbVQ8p21suUOIjvs2yDd3UWZ+XS3PP9EizRO6JDd9pomI8fRX4pYEONsMs1ZNE5KNXYbnMFLfHv4jVT+Tjbe2AaRHRc7juO8fQpF+dPipXL34nnSXZ2Vnevr5LhxE2V8EuclkmIiJanweMlxHAfH2bzmpE56dF5FjA1A0COF7iqZ/Wxenrm/WTo6VNdovXefWCPDRldLOp3U5Xy8q4odd1zeJBbRiR3gYndWnri3TV54PCfZVJUc9J4G6ejJy4sz2mXRvB69xgU5/OQJUt9AamE+ThkshUgO176kVp0+VM5ghtvlrMTFjuM4a8WsfJecO3OO5LVRPKy+Rt4zaZLUqrhJRkVtGBPSrVa31rNlHcfphWiOihtcD5zpBKlrsTseMfBAqSj5tqzMeq5Dnn+yTTqW1ksy3SF1DRlJZzIiafrtpKw4rw/uHc+a7Opij5tLUugpqNxUwZnVqV7DYcNrZdK0SCZOq5WmURlJZVWAEs0pIUZVcCZV9NjRUpLSdbpGyxu5jZb7Fs866x6/9KvgYsfZKMA0Y5yTUZw+QSmSWqV/+Slbpf+4Q/5a1Omw62UNnOg101m9VmkVMkVtzFqLkVy/tFnuWLFExqVKcuqm02XzVEYKem0ZPYmnguyT9siO4zi9BDusBrjsPBMxiJ1r3aZ2R+ck35WWhbPzcs/NLTqf1T0ojMTWpftgjGK75AS4plyTSpdu5TyeXibJaHY9kkgVJZHOy04HDJMR46qlcWRR0lVqsyWtjiF2X+8A11cPaYNI2BGSkkT9lFvU14d68V5vlspYXdw3iHPWdeXD2L3X/8K2vrCN+sk32ZZHpWiNdSvP5Y1Y0/msiXDst7rfW2IAD70h4mLH2SjgL7ygBiZVNjOYdP3Tt/Xqo+svgfVuHV5LLHbi0ZL0Otol0nXFhCxLidy3ZLHcuaRNuostcsK0zWWP2iapiUraOMZPBGlGbBe/tI7jvGlU/PCgpaQWO5+UF5/qkgWzu6StJS+5bhzvHrXXWJc359RuVMRGejU2V69YMim5nqQUcylJRCnJVkdy9GkjJVnLVm0ItU3kARVt4/oguKImWPRcw3yA+cpzC9tWd76v9x0qjxn7AaseF1hXuT68rJN1zPNC1b683mcGKj+7UCj0fk8InxEIn7+6z3LeGnodXew4Qx+e4CSKjENDmkR4rhLFy1pSauCTPFl0VkUvSU7td0ELQjGjpqJTr9dv586Sl1q7pJis0uvaJudus5OMYnhpnsriqCSpndT/eEqrVzgRv1PDcRznjcAjicwcq+1IFtQBz0uxqHY6UaU2Ru2MbdN/3ti33Ph4TTu26nIpn5AFLxflP7fMlkR+jKRqmmW7XRtl+k6NksxyQdef2MH5xx3F4Q/CgnWcTxABYYowqBQgCAKWw3wlfb8Pdai7dOlSGTVqlB1jdXUCxWJR5s2bJ5MmTZL29nZ59dVXZdttt7V9KutVzq+J8Dn5fN4K+/D5fAbnw3mNGzfO6rGObXV1dbaP8/bR6+lixxn6FKUgOW0s729tlmc6OqSU44mJDYysqPEh/7tPo+Bow8JTPjUPxVRRr44aZV3u6irKs4VOyWczNvDAnk318vFRm6hTojW0Hk9biQQhJJMqfhJqvBNJFzuO47w5cEnMGpvjToSHwU6w06wEnbHU4zeTTrURofbZ2rMKGE4gkMTRJq9Y6zzzQKs8eHuXVFVHUtOQkHfs3yibbFGlWhLHf2V0YV1y9913y6JFi+SII44wJz+Tycjf//532W+//WT06NG9ooS/D0QQYgDCOkQOx9h///1XETxsr4S6r7zyinzjG9+Q008/Xfbdd9/XCKRKt7izs1Muuugi+fSnPy3333+//P73v5eLL75Yamridw1Rl8945JFHbPn1mD59ujQ0NNgxV6xYYeImnP8VV1wh3d3dcvLJJ5drxyCynLVDr7GLHWfoQwzn1Zac/G7hK/JwMpJsMSvpqGB9TzD8eTXwTJ0+qGVIlyLrNIx4SamQyebTUpMuysh0QrYbPUr2axouk+zSabOql5GITipKkOlmlzRVUGOeXj+Np+M4Gx6xg86gBcEqqyOqNkW9FVuSBA9fsCluV1ZBL88aW7GwwS5hXnpa03LLFYulKjlMmlc0y8gJIru8c7gMG0MUhaGmB56+rud5551nAucTn/iEiQD46le/Ku9973tl2LBhtrzllltKNpuVhx9+WBYsWGDHSKfTsvvuu1ud73//+3L++eevInCoQ9QEcYFgCp/7f//3fyZ6vvnNb0p1dXXvPiNHjpT6+nqZM2eORXIQINdee60cc8wx8txzz8nNN98sn//85020TJgwweqy71lnnWXT1bnUYf2ZZ54pW2yxhTz++ONyww03SE9Pj21DuL388ss23WqrrVbZ53vf+94qy2HeefPo9XKx4wx98mrhi6WEzOnokLldXdpEkmCV06LGA+ecCIbbjteAYUiZ0xFJvixkGrQh3LyuXoaltZGxYWAzkkxQiygQReuVryWTvP6T8WvrOM6bBcNT6ZWY/dAVr7EjblhWpe+Fg1XXmZAspiVSt6+9pSD/vrJVJm1SJa/OytsDqj0PUQd+2roTOxSEDeVLX/qSfPSjH5Uf/OAHcu6551o0Zfjw4XLccceZCPj1r38tP/rRj6Sqqqo35W358uXy2c9+1kQOUZ2rrrrKhE9ra6ssXrzYUsLOOecc+clPfmKpaB/4wAfsWOwbIkUsM0+59NJL5YADDpCjjz5avvOd78gee+wh22yzjVx99dV2Hs8//7xcd9118sUvflH++te/yiGHHGKRIUQa+1eyOkHC9+Sz2XbvvffKfffdZ+v4Pi+88IKltu244452PEQW57LXXnu95lirO7azZvR6udhxhj5x/jeGJu5/wjvpkgmS25Jq/IlY+DPC1aLXjStkTaSqGJ61pVXJZLmIyaKuK+o0rVtVMFooR2vqhJGVuJ4IINsn3uQ4jvPG2EtHSTPGilAwIFosslM25vZExQ3Lqui1CdGvXlZdpueqRNhs1Tz5olz1q3kyfXqTFHpS6mx3ytStG2TvI9dNH5HgeiI2iKB87WtfkzPOOMOEDpGTRx991LbRRwbHf7vttrO0M/YLpaWlxfb5+te/Lt/+9rdlzz33NKFCStltt91m4oY0uMsuu8wExcEHHyxLlizp/WxEAwKDaA7CCLGz+eabWyoc5/G+971Pdt55Z7nkkkvsczin3/3udybEiETxeRyf82tra7NjVh6bgphBCDFlmT44pLERmVq4cKFFlYCIUVdXV28aH8cZM2aMbL311r2RJwqEqfPm0OvlYsfZCKDt1MIfesmcdDq7qhHSBpO2weyG247XotcGn4L4F+nxzJP4h8VgFDu7ZKxLJiTNNdYNJfrucFH1f4bzjkf3oaLjOM6bASsTpxivFDwYlICut0U3LK/hNWKnD6V4XFIb5lvnL79orkweP0ymTK2TJx5rlvYOkQ98bky58sCC8w+IENLDfvrTn8oXvvAFEy30i0EQ/PKXv5SnnnpKcrmcRTw+97nPWbQHcdHc3GyRHSJB9IVBLBx11FHy5S9/2aIvd955p5x99tmyySabWBobQuKxxx6zCBAiivQ3zoEoCsdBzCAu6IvDdtLHdt11VxNZ9B16//vfb+fC53AeRJHe/e53m9jh8yjh+7B/iEAhpmpra028IHTe9a532bnPmjXLUvJIX0MokYbHMufAftRH1BDtQoAFgcM0zDtvDr1eLnacoQ9/4iXiODjs2m4SzSkwQpj+5WcxuOrJl7wT/WvhumFY40uk/4jkVeWky35IUbdxTfFF4uew2oxyLVVZYlSSXGxd64bZcZw3C9Z6VbAfGBpgPl52q7I6sLmvg4kdSEmhmJdb/twtpZ687LJPtcyfU5QZTxXkpC+PsBoDDe0yogARQuf8J598Uj72sY9Z2lkQE9OmTbM0sY6ODouq0NclRHcuuOACEz1sQwwQAXn22WflwgsvNLFE2hr9f8aOHWv1ERCIClLcAogc6u6zzz5y6KGH9va/YT2iicgL4oqBEzgOn8W2iRMn2jHpg7P33nvbOuryGbfccovNn3DCCfLEE0+YCOJciV4hgBhsIaSu/epXvzIhRjSKvjwIL1L1EEhEuoAR40L0J+Bt6lsDrZP6DomJjjOEwTDon7q2AymbMtoMqWsp7AUvFyUCQT0vqxaum031n1i36HXTdXrN2Fa+dLada8loP7pWC0MZxNeZeo7jOG8WrMiq//VdFy/zr5e+5fWJXxRKOlVSIm0Lh1Un5OVn2qSnEMn2+zRJIWqXF59ZKpOnNOp2FUZ6yPjISKR4YIiSvWT0DUTVmwTBADj6RF0Y0vn222+3CM+UKVPk+uuvN4HCeqaMoIbQoH8LaWCknZ100kly4IEHyk477dQ7qMAdd9xhAwogghAq1EMs8Rn0uyGqwrobb7zRIjMMXoDYog8NgxaQ1oZQOfHEE+XDH/6wCTL66Wy22WaWBkcK2+zZsy0aw/kwRcQQwXnmmWds8IIjjzzS+g0h0D7zmc+YaCFqg3BBVCHUGAWOQQoY5Y39EDsf+chH7HuzfZdddukVYJXFeWt8V+mfv1jHcRzHcRxn0MIrAhL0tVR4WFXTlJTho+qlealIR0deNt2iTprnV8uyBXTaR4jEIX2yIWwIcF3Vn642jjupW4gDhE/o20IEBSGC0CCVjDSyBx980IRLSPGiLpGhuXPnWiSEqAkRGiI1CKWpU6faZ3A8UuIQLAgI5unrEwYVQJDweWxnyrF+85vfmJghZY3+OvQBYoAEBirg84geEUX65z//KQ899JCl2fFdOPb8+fOlqanJzqcvHB9xw/lzHL7XzJkzLSrFwAqczz/+8Q87d6JdnIfTP7jYcRzHcRzHGeqUVOgQriFSo//XNhSlYURSnfCStDYXZNTYauluqZZXX2qTYk5FTkQ0R0HrMI1lT78TIjw4+0RJiH7QUZ9Iy0033WQRGtLCiIAQDaE+5a677rJ+PURjgOgJYoMITGNjo9UdP368fOUrX7H+O6SmMeobUwYeQFQQLWKZaBKpYwgs+unwedRhf0ZEI6WOlDVGYNt0001tSGyW+Uw+B1GFGCOFjSGp+767Bxg04Z577rFzR2TRn4iIFKlyCCrED32JOH9GmeO7OP2Dix3HcRzHcZyhToKelRl1tnH+CpKpzcqkrbKSqUnIzKcL0tOTkLHjk/LC4+3ywsM9koqyK9OmLKwTiUSvdeL7A8QCaWCMdIboQRCMGDHCojdEUZYtW2YDEJByhjBgUAMiQh//+MctBY2+PAxywPtzEBKkjvEOHc6f4yE+mBKF4dhEd9hGQWBQ2E4h3ezpp582cUU9okuktDG6GxEYIkSkxBGVmjx5skWJ6JfDYAmnnHKKHH744XZcPpNIVIDhptmXVDvOge2HHXaYDWvNZyC+SF1D5NDXh/5KTv/gYsdxHMdxHGcjAOlCnyfrX6kLNQ1JqatPS2cLLxstyfQdqqVQjGTBnIK0LFVxgzIirtM7Us3AEEQIAoL+MkRs6FvDMNAIGUQBIIjoo0OkZvvtt7f+Lbygk3fSMGQ1ggFRQoSmcjjoMCgAo70R6bn11ltlt912691OCcLummuuscgQwoVBE8K7bhBCvHuHfjVEXx544AEbCAExhjBCeDEcdYB0Oo7LoAsIMUQOESKEDOlq9DciekV06corr7TPZGQ5jvOe97zHXmbq9A8+GpvjOI7jOM5Qp9fdw6lntM2idLQk5Ym7OuTVF9tk1/1HysQpGbnzxuXSvLRbdtt/mGy+cx2eotYvj4BXSse7ryVBYABCBKef4aWJ1hBVoTBCGuKGqAtREAQH+xDtoSCMiPggIhgtjTqso98N9RA7DDYA4fNIFaN/DtEbBidgAIBwHkHskIrG5zIMNRC5qQTRRN8bPheBwjDXiCwEUIgihXoItxkzZtj5IoSow+AK1GNQAyJEfFfe80NK26RJk3oHLyAtjsiRs3boffWhpx3HcRzHcYY+8WsBUCsEaYr2PoaUzH22VR66pUWGjxktB34wK23Li3L3zct1GsnxnxolyQxpZUmtq/sle3T/13a+f6v0dT0RPAgApoA4QGT0FSIsMx+mlVRug77bgeOGekGU9N0nzEOo25fKehwzHAsqj8X3CZ+JEOt7vLCddRwjHJdr0beu8/bQa8jAsY7jOI7jOM5QRl3n8pyis5bOpqqnvjEj9U0N0rKiG89QahpSMmWL4VKMktK+oqA7MrABIiSyl3GbYuot/MMIb6FQb5UKayz48bEvT/8V3NHYyWc+m42FTlyHSiv3gZXr9F87B/bl+zDQQTwN+4R6kE6nVETRRwdxEo63cnuYR4S89ljxNCyX7JqU7FjxOojPgwLhu1RV0f9p5fHCdwvbOafwnSq/WzztW+J7seYS6jkBFzuO4ziO4zhDHpzolf/amAOlvFTXp6WqKSVt7XEfl3S2KOOnJmTUuIwseEmk0F2URKRCRncoSkb96D5ONctBEFlh3esXO4c+80wTdry4oBfCunhaubyyfqgX9lt5rMoS79O3zsr5lduZpjhoeVu8Lhxj5T7xu+X6HmPV5TDft5gW6rMu7B/2W+P+rH/D4lTiYsdxHMdxHGfIs3onuLomIfWNuIMqVMhvK6WkYVhaNt2ySl54ulNaFmVUw9BvhddKR1JK8sJRnar4Ubddi26XbHmaLq/zMnAl9bollndOJS52HMdxHMdxhjwqZHCESUVToRKnS6UlmU3I+E2rpbaBWEKBXCtJpUU2365W9U2n3HzlPHnqvjaRYo+kS0nVQ1ndnZeMEtmgv0khLnr8EJmI570MSFHN+npF/y0XJ+Bix3Ecx3EcZ4izigtcdoqZUBqHJyVbVZKWZpZUFCWLklTBs83OIySTqZZnHy3IjEc7dVtOd2OQAp1SDzeylIpL79H1GOHDvPR/sev+esXpi4/G5jiO4ziOM+TBES57zOr6EeCJ+4GodOlIyD23zJdJWw6XLbapkiiRl2QiI5IvyTMP9sjTD+my6pqjTq6XdIMKIRYSST0Sz8zNA1fKQsmmzromvuokujG4g87GYR4jjuJtnOh396GnHcdxHMdxhjzB20swmAB9P4q2qlREtIg8/2izzH65S959zAQppVW0qKBJSEESEdGbpMx8pksevGOZCqCEVFdXSTqTijvaJwocVTEPWye20tY4A0CfS0vPKRIKmfL/vsdXS1NTI1pURU9kQke9fa2JMN34cLHjOI7jOI6zMRC8PcQJYkdFj435VWTgAZH5L3bKY/e1yCFHj5GqYWyjX446yJE6y8m8RJKXFx4uSct8kebmDsnnIolUCCWsUzyUP4BBDpx1RuzG6x2M/1exUyXDhjXFy+XojosdFzuO4ziO4zhDm+DtJfI6n1KxQ0RGPWIbaS2S9sUlufXvy2W//6qVUZsyqlrGnGQTPFY3J1G+RnKdRenpRuiUtHBAwM0OBdy1HDjCNa4kiJqEDB+Xtvf5xGvCeqYudhzHcRzHcZyhSvD2EDtQyqjgQa0UVcukVO8k5fKftso2e3XL9nuPjqunETskSamDnejSOjUbq8/sbKCgdfxP1nEcx3EcZ2Ok/Ly7KJGKGxU2yaS0tuQkKqiTaNlplVEEXbG6oILjDHJc7DiO4ziO42w0oFj6qhYVPcmSFIt5aVtRlJ4u3a5CyCI6vXXTWjwZyNnwcLHjOI7jOI6zURG7fwwdjaBJpRiEQEVNqihdnUnpaCPOE3fIsf4elFKinPbmOBsWLnYcx3Ecx3GGOr1BGly/SvdPV7I+WZIpm9ep0EnKork5EzdxIKfIPyS56b8udpwNDxc7juM4juM4Gw2meMrix/4pl5KMHpeWQr4grS09UizE66yY6AF3G50ND/+rdRzHcRzH2WhAxBChoaBiWOYlo0kZPpJ0NpHOjkh6OkO9AHXdbXQ2PPyv1nEcx3EcZ6MC4VIWO/TFIWVNRU/DqJSMnzBSlixqkaWL28r1Vk4stc1xNjBc7DiO4ziO42xU4P4xtvSq4iVZV5RhI0SK7ZH0tDL6mm4vpaWok7xVLb+jZy3hFY9RFNk0zFcuF4vF3mXmmc6fP3+VupV1wrqXXnpJurq6bN2aSqFQsGPl8/nVbq8sHHPBggU2bW1tteOH86ksrHujEupyLD67p6ent8ybN0/mzp0ruVyudx11nP7BxY7jOI7jOM5GBcqlXPg/nlgKW0NjRpKplL1vJ7yHn63xf/0Ljj/i5LHHHpOHH37YBMXixYvlvvvukxkzZkhHR4cVBMof//hHq79w4UKr+8ADD8jMmTNNSCAMli9fLueee67Mnj27V8hAECMICI7D9i984Qvy73//246HwKAwTwmwT1tbm/z2t7+1c3zwwQflW9/6lnR2dq5SDzifNyp8N86FYyGgEFyh/PnPf5ZLL710lXUUp39I6IUPf8mO4ziO4zjORkoU5aRlflL+fcMySaZLctSpo3RtUoomexKSFt42SsRn7QjCApGBqEkmk/K3v/1NDj/8cFm0aJG8/PLLJjbe8573mMg56aST5F//+peceeaZcuONN5p4QHRsv/328sEPflCeffZZ+dnPfiYHHnigPProo3LYYYfJ3nvvLdlsVi677DK59957ZeLEiXbMlAq59vZ2WbJkiUyePNnOh89funSpHHHEEbLPPvvI+eefLy0tLdLY2CjPP/+8bL311nZeCKWdd97ZxNSJJ55o8xyPqMwbMWbMGKmqqpJly5bJCy+8YFPgnP7zn/+YGOO8A8OHD5d99923vOS8XRKKR3Ycx3Ecx3Eci/BkahNS15CVnm4VOFFJV0a2PnYY+8dtrIy6qC9qooQCCA8EBAXYDiwzz/a6ujrbd9ttt7XoziWXXGJi4uijj5Zdd91VrrvuOrnppptMSBBFqa2tNeH03ve+1wTN+9//fjnrrLOsPuvYhoAhqoQIQwztv//+8qEPfcgEFdNDDz1UJk2aJCeffLLU1NRYHepyHoimNyoIHeqOGDHC9nv66adNpFEQWkSmWIf4e+KJJ6yO0z+42HEcx3Ecx3EsaS2dTUjj8Cop5IpSorOOwr8r5/oXBEAQDZXT4OyHKesDzNfX10t3d7ecd955JlQQLizvvvvustVWW8nVV19tKXBjx46V7bbbTjbddFOL1FCGDRtm+1PCdvZhPYIqk8mYQNl8881l5MiRssUWW9j+1dXVJrAaGhp6z5XPRCRRiBZRKufDMoKG82lubrb9d9llFxNmu+22m4wbN05Gjx5t63baaSf7Dpwn0Z7Ka1J5DZw3j6exOY7jOI7jOOpM41BHMn9mQe67ZYkc9sFJUj+Sl4qm1GFU4UFkpR/0TnA958yZY/1VEAOkiI0fP94cfPrK4NyTJsagAJ/5zGfkzjvvtDS2m2++WR5//HETDR/96Edl1KhRJjiI4vzyl7+0KAxCgUgPESAiJsB2+stwXCIziA/q77nnnnLQQQdZZClEk770pS9ZnxmiMKSvIUboc8NnEt3h/D/1qU9ZytuKFSvs/OkP9M9//tMiSccff7w8+eSTcu2118qFF15o34fIDscjMkX6Hml7RKX4bAQOQuqCCy6w6WmnnWaiC/HFeYXoFlTOO2+MXi9PY3Mcx3Ecx3FAHWn9v7YxKY1NVdLZnpdIGEmsd2u/gFhAdJBeRsRk2rRp1keFaAp9a5inTJgwwZz9dDruJ8R+iBYEA1GZu+++27ZTl8gI21mPAKIeIGz4HKIpCCAEFSLje9/7nkV0jj32WBMV1ENoIIiozyAG9ANCjFx00UXy2c9+VrbccksTL0wRZYiWpqYmmT59ukyZMsXEFfuG78P2TTbZxCJDRIk4B4TYQw89JNdff719X9LWvvnNb8onPvEJiyKRNsf5UJcIk4ubtcfFjuM4juM4jqNqQiRSwVBVk5SGxirpaMtLiSyystiJ+tHvRpggDhAcCAoc/4MPPtjSuhgQgMIgA4gJ6gZw/llGPBA9+b//+z+L/HznO9+R5557Tn74wx+aeDj77LNt5Laf/vSnJlqImiBULr74YuvjQ7SF9DfWs/3HP/6x/OlPf7JUM0D0MAgCUJfIDQKKKdBnB8HD+SC+WE+EifMlikOUCPHEdsQa0xA92muvveTrX/+67fPiiy+aUCJqRUTnlltukd/97nd2bI4L4fu78Hl7uNhxHMdxHMdxyqGbpGSrStI0Mi3NiwuS7y6p1om0FBmroF8IzjtTnPoAAoO0MJx6oiJsIwIElY4+IoF9icaEAQY+9rGPydSpU23wAcqnP/1pEwtEfIiyEFEJkZcgRJgiTthOihnTP/zhDyaSGP3tN7/5jUVemDLgASO0kfqGQCGt7pFHHrHz5HwQRozKRkQmDEYQhsBmO4KJOggmUvM4Dml8iDvS2BBZRHuIZjHAwq9//evyt40HbXCh8/ZxseM4juM4juMY9MlJZIsydmpGZs/okM5l6iom1GlPltRpXBlhWRtw3HHgSdNCWCA0gsBhdDJS2xAJiJFTTjnFloF1FPrFICAQNL///e/tGKSWkf6FuOEdOvQFYvCB008/XT75yU9aH5szzjjDlhEXRJKIprCedRzruOOOk+9///smRBgGm/Pbcccd5Stf+Yr8z//8jw0cgPhi/ic/+YkNdc05ImSIMHH+Rx55pK2DIFA45xA5QuwwyMEee+xhI7udeuqpFvkhKoUYIzr03e9+V0444QTb30XO2uNix3Ecx3Ecx1FwrGMHu64hJYV8QpqXFEQilTlaJBH3g1lbOD6igUjHK6+8Yh376UfDyGUMDLDZZpv1RjOIvCA6EAwsIyQQKh/+8Iet7wtC5wMf+EBvXx765TBwQdif/YApQoIpERq2VRLq8R4fUuGuueYaixwhSjgWn8t7b+jz87//+79yxRVX2CAHbEPokFKHWEJghfMkssM8YiaMDEf6G4MsMGXgA64D9RBv9O2h384vfvELe7Gq0z+42HEcx3Ecx3EUBIWWUlKy1SLFSGTpooJEhZRuiqTUT2IHECeMYsZoaQgaXg5KChuDC/Aiz9An5uc//7mNjkaKWtiP9QgI+sAQtSGd7POf/7zty7EY5IC0NkDEsA9i4qtf/aoNNICgYRS2QKUouvXWWy06xIABiCaGh0bQUBgaGpHFMNW8C4eR2niJKZ9PZIiUtACCDSFD3yGiRYgdBjIgRY0UOI5z++23236XX365DayA2CHSQ1SHbU7/4ENPO47jOI7jOGWHP6czWRbkzmtaZO6sbjnkyNEydrpuIlrSD8/J+7qeIcqyJpeU9ZWRGJYRHwGW+9YJAqZSyITp6upVUrm9L6s75hvVhzXVqdy/8rjwesd13hx6DX3oacdxHMdxHEcdb/sXB5sSyYjxaRuNbd5sFUBRStf0j9uIE19ZAn3Xh4Kw6btcyerqhPVhSqHOmur1Xbcm+u7T93h9y+o+s7JUbqs8blh21h4XO47jOI7jOI462PyrzjeyR+cnblIndfUlmT+7VfLtQQw5zoaFix3HcRzHcRxHLIOqlFKhU9BSkpETRHbbZ7S0Lo3kwTuXqthxueNseLjYcRzHcRzHceKIjlKilwNhHi2jN0nLyE2q5NVXcpKKGKBAC6rIhBHzFJ3ndTha4nfylDd76fdi/4brX77mlmtI6b/xI4YULnYcx3Ecx3Ec66kT57JR6DhfkupGkanbNEpXT15Knal4COpefxt5lItLoqBT9bbNAdeNXgakRPZfuP7hha8MbIA41Q3Oa3Cx4ziO4ziO4xhxdMfcaVtKJCOZtlVaRo1Ly0sz1LlWMRRZ1CcWO5Ko0pK2uiEaVJ54GYDS67qrELX3HpFyqCIz0uUi65zX4ENPO47jOI7jOArpUOE5eGTBhIQ61wldXShEcvkls6Smqkamb9MoEzbNSjJL/XJ1UG889rfNK3cGgBI3I57RW5SUqtqk1DQiMOlnpaLTB1pehQS42HEcx3Ecx3FMuVSKFRzrYnCe8/LY3Z3yylMl6e7plHQmkmSKyjjf5fq6mCildMnFzkARIWqSeZ3JSqlUI5O3SMnO+zZJpkovfirlOVt9cLHjOI7jOI7jlMElZMABPGYtiJ0I4aIl2S09bVUyb2aXzJ/TKa0rklIqZnQPdbyNuF6cBudiZ6CwEfESOZ1TYVPKyPipRdlhj2GSzup9S6rQTLraqcTFjuM4juM4jlMGlxBHmtlMhWZhmK9ISlE6HoiglIo7xLOu1KNTdbwtpMA6+pA4AwaX2IYH516Vyi8lDS98TUjaheYquNhxHMdxHMdxysQOdIxOcaptWUVNoiilYta2BEc7rq7/xD3ny7DSGShMY+o/FkHTeXXl7fpHUVn4xNWcMi52HMdxHMdxnJhejxBHWgvpbKzTeSI6sfjBnS7GzjaY2CEaRPQnrbKo2lY7A0PC0gwRO9wbIjy6spTXVazT5aTLnUpc7DiO4ziO4ziOMyRB63gvJsdxHMdxHMdxhiQudhzHcRzHcRzHGZK42HEcx3Ecx3EcZ0jiYsdxHMdxHMdxnCGJix3HcRzHcRzHcYYkLnYcx3Ecx3EcxxmSuNhxHMdxHMdxHGdI4mLHcRzHcRzHcZwhiYsdx3Ecx3Ecx3GGJC52HMdxHMdxHMcZkrjYcRzHcRzHcRxnCCLy/wGLzhoWWgxxiQAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "ec1e695e-8bb2-47be-bf84-683db3d6c3a5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "![image.png](attachment:17473f51-ae4e-4941-b141-c76bf65bc710.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d56c4630-e41b-41aa-888a-048e716190ac",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## <center>内容摘要<center>\n",
    "<font size = 9><center> 一、列表 \n",
    "<center> 二、元组  <center>\n",
    "<center> 三、字典   <center>\n",
    "<center> 四、集合  <center>\n",
    "    <center>      五、字符串    <center>\n",
    "<center> 六、序列   <center>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be5581a6-7d70-4f7a-9e2d-9ce397b8c44a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的定义</font>    \n",
    "Python中和数组相似的数据类型，就是列表（list），**是由一系元素按特定顺序构成的数据序列**。不过列表的功能要比数组更加强大，Python中的列表可以存储不同类型的数据。同一个列表可以包含：\n",
    "- **数字、字符串等数据**，\n",
    "- **甚至还可以包含一个列表**。\n",
    "- **列表中的数据可以是重复的**。\n",
    "\n",
    "列表也是一种结构化的、非标量类型，操作一个列表类型的变量，除了可以使用运算符还可以使用它的方法。包括**索引和切片、拼接、重复、成员运算以及比较运算**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "884ad0e7-603d-4a8e-b589-c7e838781dc8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的创建和删除 </font>  \n",
    "- 利用中括号 **[]**, 列表中的多个元素用逗号进行分隔。\n",
    "- 利用`list ()` 函数，`list`并不是一个普通的函数，它是创建列表对象的构造器（后面会讲到对象和构造器这两个概念）   \n",
    "  列表中的数据称为 <font color = #DC143C>**元素**</font>，可以是多种数据类型。一般情况下，只在列表中定义同一类型的数据，这样可以提高程序的可读性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c2a2ff0-ed6f-47ca-b8ed-d57fd4997bb3",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n",
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "        items1 = [35, 12, 99, 68, 55, 87]\n",
    "        items2 = ['Python', 'Java', 'Go', 'Kotlin']\n",
    "        items3 = list(range(1, 10))# 借助range 函数\n",
    "        items4 = list('Python')\n",
    "        print (items1)\n",
    "        print (items2)\n",
    "        print (items3)\n",
    "        print (items4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7c99846-0a90-432c-8ba7-24805120cec0",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "```range (start, stop, step)```函数返回的是一个可迭代对象,在range()函数中也可以只包含1个参数stop，其余两个省略。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b84153c7-4471-4472-8e42-5b8e01ea1512",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**注意:** ```list()```括号内只能是字符串、数字、或变量，如："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83576fae-eaac-4a70-a872-0b403ba7ca71",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n",
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "list(Python) ## 不可以"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5f24657-cb59-4908-a191-03e9af1bc44c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "Python=[1,2,3]\n",
    "list(Python)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24b2c444-830d-4252-a740-0ba7b1edbfed",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**删除**：```del```语句，后面指定列表名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e03dd2a-f6e2-46cb-b2f8-e231e8d5f065",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print (items1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3f5a990-53af-4cc3-986b-2dd7684166f2",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "del items1\n",
    "print (items1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3021e21-32c1-435f-9d2e-a600a4e31371",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "_____________________"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1903544-bb24-4467-a6cb-a3b6ba455026",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**需要注意：**，列表是一种可变数据类型，也就是说列表可以***添加元素、删除元素、更新元素***，这一点跟字符串有着鲜明的差别。字符串是一种不可变数据类型，也就是说对字符串做***拼接、重复、转换大小写、修剪空格***等操作的时候会产生新的字符串，***原来的字符串并没有发生任何改变***。"
   ]
  },
  {
   "attachments": {
    "d293fd40-564a-44a2-a5ef-0802648857d6.png": {
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"
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"
    }
   },
   "cell_type": "markdown",
   "id": "b5d1ba3b-ebe0-42ae-80b6-b69e48aaa6c4",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的索引 </font>\n",
    "**正索引**：Python中的索引从0开始计数递增，也就是说，通过索引0可以访问到列表的第1个元素，索引1可以访问到列表的第2个元素，以此类推。   \n",
    "![image.png](attachment:d6fa2671-ccd3-4482-88ae-98454dfcff16.png)\n",
    "\n",
    "**负索引：** 当索引为负数时，是从右至左开始计数。也就是从列表的最后一个元素开始访问，对应的索引为-1，倒数第2个元素的索引为-2，以此类推。注意，负数索引从-1开始。    \n",
    "![image.png](attachment:d293fd40-564a-44a2-a5ef-0802648857d6.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc195eb7-ce8e-490d-b868-9217e06a1fed",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**子列表索引：** 列表1中包含了另外一个列表2，要想访问列表2中的元素，需要使用两次索引。定义一个包含列表元素的列表list2，如果想获取内部子列表中的第3个元素，应该先指定子列表在list2中的索引，再指定子列表中第3个元素的索引。     \n",
    "\\>>>list2 = [23, 45, 36, [2, 4, 6, 8], 54, 73]     # 包含子列表的列表   \n",
    "\\>>> list2[3][2]    # 指定两次索引    \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54678e74-ba19-44b5-bcd0-8f2191dc1f7a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的切片 </font>\n",
    "切片：访问列表中指定范围的元素。    \n",
    "格式: `列表名[start : end : step]`\n",
    "- start：起始索引（包含该位置），默认值为0。\n",
    "- end：结束索引（不包含该位置）。如果不指定该参数，则默认结束位置是列表的长度。\n",
    "- step：步长，默认值为1。步长为正数时，从左向右取值；步长为负数时，从右向左取值。如果省略步长，最后一个冒号也可以省略。如果省略的是start和end，则需要保留冒号。\n",
    "> 切片也支持负数索引，也就是按照从右至左的顺序获取切片结果。将步长设为-1时，列表中的元素会全部翻转（在不指定start和end的情况下）。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ab57e52-5b49-4ebc-a2db-60c678573660",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### 练一练 ###\n",
    "\\>>> num_list = [11, 22, 33, 44, 55, 66, 77, 88, 99]   \n",
    "\\>>> num_list[2:7:2]?    \n",
    "\\>>> num_list[3:6]?    \n",
    "\\>>> num_list[3:]?     \n",
    "\\>>> num_list[::3]?   \n",
    "\\>>> num_list[::-1]?  \n",
    "\\>>> num_list[::-2]?   \n",
    "\\>>> num_list[-2::-2]?   \n",
    "\\>>> num_list[-2:-7:-2]?  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2d6249be-8da1-4e51-a85a-9e8da148069f",
   "metadata": {
    "editable": true,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n",
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "### 练一练 ###\n",
    "num_list = [11, 22, 33, 44, 55, 66, 77, 88, 99]   \n",
    "print(num_list[2:7:2])\n",
    "print(num_list[3:6])    \n",
    "print(num_list[3:])    \n",
    "print(num_list[::3])  \n",
    "print(num_list[::-1]) \n",
    "print(num_list[::-2])\n",
    "print(num_list[-2::-2])\n",
    "print(num_list[-2:-7:-2])   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67dd7178-5b0f-4d0b-8eb9-d3f130d5e9cf",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2922278-f93f-458a-ac7e-7058beb92012",
   "metadata": {
    "editable": true,
    "jp-MarkdownHeadingCollapsed": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 修改列表元素</font>\n",
    "- 可以通过索引修改列表元素，就像为变量赋值一样。    \n",
    "\\>>> str1 = [\"name\", \"age\", \"num\", 67, \"address\"]    \n",
    "\\>>> str1    \n",
    "['name', 'age', 'num', 67, 'address']     \n",
    "\\>>> str1[3] = \"score\"              # 赋值新元素   \n",
    "\\>>> str1    \n",
    "['name', 'age', 'num', 'score', 'address']    # 修改之后的列表元素   \n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97460625-723e-42c9-9ab4-93d7a7ee17fb",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 删除列表元素</font>\n",
    "删除列表元素主要有四种操作方法:\n",
    "- `remove()`方法、\n",
    "- `pop()`方法\n",
    "- `del 列表名[索引值]`语句\n",
    "- `clear()`方法\n",
    "  \n",
    "`remove()`方法并不需要知道该元素在列表中的具体位置，只需要指定一个待删除的元素即可。如果指定的元素在列表中并不存在，则会出现ValueError错误，提示该值不在此列表中。\n",
    "\n",
    "`pop()`方法可以指定列表中元素的索引值将其删除。该方法是将列表中的指定元素取出来并删除。如果不指定索引，则默认删除列表的最后一个元素。\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daac1f92-3f3a-46e4-8b92-bc366b5816ef",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的方法</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a11d2af-6083-45a7-bd13-ec1ac8ecf063",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n",
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "items1 = [35, 12, 99, 68, 55, 87]\n",
    "items2 = [45, 8, 29]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48841451-5521-491f-afce-0d20f0da3f84",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "*****\n",
    "**列表的拼接**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e936150-01c0-4d60-8c42-c95a7941c51d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items3 = items1 + items2\n",
    "print(items3)    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c90eb819-cdf8-43ca-b870-242bcb5973c9",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65d78189-a8cb-4500-bd61-603d53637639",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**获取列表的长度(元素个数)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16d78ee4-7832-437f-9958-84f97523dac7",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print(items3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03b08176-4066-4b06-a0dd-4fd915479ada",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "size = len(items3)\n",
    "print(size)      "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77c5caf6-1dca-4581-a896-493f20dc349c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**列表的索引**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb1f3e31-ceb7-4a64-b19e-1f61a3ebac1e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print(items3[-size])\n",
    "print(items3[0])\n",
    "print(items3[len(items3)-1])\n",
    "print(items3[size-1])\n",
    "print(items3[-1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e7ebb93-be34-4959-aab8-32ab6d335c85",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**列表的重复**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b84da55b-00f6-4f49-8f20-515f59e236be",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items4 = ['hello'] * 3\n",
    "print(items4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecac6051-acab-4e9a-84dd-211c2dbf0164",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**列表的成员运算**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c3aa8b5-60fb-47b2-bde5-9d2137250888",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "print(100 in items3)       \n",
    "print('hello' in items4)    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05abd4be-31ca-49db-80c5-a15d79ff6c1c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d31e0971-79b7-4790-9a17-cb2be4722542",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**列表的比较运算**: 两个列表比较相等性比的是对应索引位置上的元素是否相等"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b265d9f8-af4c-4618-bc4f-5cb823a113a8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items5 = [1, 2, 3, 4]\n",
    "items6 = list(range(1, 5))\n",
    "print(items5 == items6)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d3f615c-8441-4945-b82e-1e8186895cf4",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**列表的比较运算**: 两个列表比较大小比的是对应索引位置上的元素的大小。\n",
    "> 一般不常用。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5f2dec5-28f8-4151-86e6-211ae99b845d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items7 = [3, 2, 1]\n",
    "print(items5 <= items7) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65fa492e-589e-4be8-a04d-66336cdb3b68",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items8=[3,1,1]\n",
    "print(items8 <= items5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e415382-f82d-49b4-99db-c2df21630fc0",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c5ced33-5639-4c0e-85d8-71ff78d1912f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items9=[1,1,10]\n",
    "print(items9 <= items5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58a7613d-a42d-417d-8d72-96c86d4958a9",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "> **注意**: \n",
    "> 由于列表是可变类型，所以通过索引操作既可以获取列表中的元素，也可以更新列表中的元素。对列表做索引操作一样要注意索引越界的问题，对于有 `N` 个元素的列表，正向索引的范围是`0` 到 `N-1`，负向索引的范围是`-1` 到 `-N`，如果超出这个范围，将引发`IndexError` 异常，错误信息为： `list index out of range`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59695085-defd-4d06-90ad-69e9ed102e9c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`Index()`方法**   \n",
    "- 格式：`index(value,start,stop)`\n",
    "      \n",
    "如果没有指定start和stop的值，从索引为0的位置开始查找，直到最后，否则位于[start,stop]索引区间。如果找不到匹配项，就会引发异常。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f30d8103-ebeb-4492-ae28-1f287f6e1279",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3caf5f36-5d3f-4ce9-8d25-6263fd0d8823",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.index('ef',0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3849191c-e834-4ed0-a5cb-5a190bea8d97",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.index('gh')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "971466ec-4932-43db-81c5-ea6b9396a64f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3ffb753-c3b1-425b-8f45-6b67483c3b6a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`in`运算符**   \n",
    "- 检索测试某个元素是否在该列表中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "236e05d9-b3d5-4b0a-8c95-deb5b637a91f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "'gh' in str1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fbd15e6-0932-406b-b355-3089de933daa",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "'ef' in str1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdb9c5a0-40f1-48dc-a125-83d1f1faee46",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c28a97ae-1519-4cf8-8a52-cf1c80940276",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`count()`方法**   \n",
    "- 用于统计某个元素在列表中出现的次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4b07d6a-7082-4b32-bcd5-fe3aa10b9947",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef','ab']\n",
    "str1.count('ab')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "04eb8134-8371-41a4-b483-3094fb90cac6",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.count('cd')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdeb0354-0ab2-4ef3-967c-5149f9db24d6",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.count('mn')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba41b276-9da1-458f-b4b4-41eb149d1000",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d38927d4-ee6c-4d95-8431-0d8570f9bc59",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`append()`方法**   \n",
    "- 追加单个元素到列表的尾部，只接受一个元素，元素可以是任何数据类型，被追加的元素在列表中保持着原结构类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cc59aac2-630b-46b9-9d55-a15307a7e8d2",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.append('gh')#追加一个元素\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c99eb964-f440-4aa2-bf11-131680d3b64a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.append(5) #追加一个数字元素\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba3a7726-6ea6-4f76-9677-c73acb4c4d25",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df3ec931-4281-4cd7-a82f-fa9f63da08bd",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`extend()`方法**   \n",
    "- 在列表的末尾一次性追加另一个列表中的多个值，可以用新列表扩展原有的列表。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1698140b-26b6-408c-89bb-8c984449278b",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.extend('gh')\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "06cf7d3c-c79c-4be6-a732-0a678f7d8f49",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.extend(['gh'])\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a3a8489b-316b-4210-9a13-e25d11f9ccf6",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.extend([8,9,10])\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32311baa-bb05-44cc-a263-360c026b4c38",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.extend(8,9)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28f02492-24cc-4634-9a95-4a0bbe3e6bc8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3745702d-72ef-4f85-8ada-420d330cd328",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`insert()`方法**   \n",
    "- 将一个元素插入到列表中的指定位置。列表的insert方法有两个参数，第一个参数是索引点，即插入的位置，第二个参数是插入的元素。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d50ed67c-cbc0-4794-89f6-2c508e868fb8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.insert(1,'gh')\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "310112d9-4000-4581-a27e-2898934460a7",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "- 当索引值大于列表长度，在列表最后插入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "857afa8d-cbdd-4294-b24a-516ff5affee5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.insert(4,'gh')\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0836d14-2c90-46e0-9713-a6c525cc5e1e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.insert(8,'gh') \n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b885003-e2b5-4f12-9eb9-4d8dff4a8cbe",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59090014-15f4-40a7-8923-e228c2ad3191",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`remove()`方法**   \n",
    "- 用于移除列表中与某值匹配的第一个元素。如果找不到匹配项，就会引发异常。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f52a9c67-d8b5-47e4-b6b8-e7be0a00c447",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.remove('ab')\n",
    "print(str1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e20cad0b-6de5-45d7-9458-6afa4af0b32e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.remove('gh')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "175786a2-45f1-4ee2-870a-5c7e458ec250",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "284f8423-03cc-41b0-978d-5dd721df940c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`pop()`方法**   \n",
    "- pop()方法用于移除列表中的一个元素（**默认为最后一个元素**），并且返回该元素的值。pop()方法可以指定索引位置，当不在索引范围内或者从空列表中使用此方法均会触发异常。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "080e84ac-0c37-4f45-b6fe-43432f183404",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.pop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "778737c9-6c5c-401c-b7b2-ae92cff9905b",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.pop(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19644fad-af74-4ae1-941c-5b9b4d53124d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1.pop(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10b5055e-936b-4a70-95bd-d3c602e5f7b4",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b9115af-c28d-45ea-8665-54773eea6b7d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`clear()`方法**   \n",
    "- 用于删除列表中所有元素，但保留列表对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2bc6b190-07b9-4caf-9211-37ebae528951",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.clear()\n",
    "str1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92143cb5-61be-4ab4-b244-893fddce9b76",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "str1=['ab','cd','ef']\n",
    "str1.clear('cd')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cfd0b6c-bf82-441d-ae53-c501bca11340",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2454c728-4793-4fc9-8509-1f7e6ac0ecd7",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "> 请注意与del命令的区别，del命令删除整个列表时，列表对象不再保留。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c302a9ea-c43f-4f95-bf21-c075e46c1b2f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的排序</font>\n",
    "-列表排序有`reverse()`、`sort()`方法，还有`reversed()`、`sorted()`函数，函数的用法请参看列表函数部分的介绍。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41d7d6b1-5569-4a75-a142-e103d79333b8",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`reverse()`方法**   \n",
    "- 用于将列表中的元素位置反向存放。列表中可以有不同类型的元素，reverse()方法只是将位置反转。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93dcac48-f3cb-4c1e-93f1-467ba98e6db5",
   "metadata": {
    "editable": true,
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "numbers=[12,34,3.14,99,-10]\n",
    "numbers.reverse()\n",
    "numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2f9689e-3264-4808-80da-5533e8b4bd59",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b787608-81e5-4048-bb8b-3482948252ea",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`sort()`方法**   \n",
    "- 用于将列表中的元素进行排序。默认按升序排列。使用reverse参数来指明列表是否降序排列，参数是简单的布尔值True或False，若其值等于True表示降序排序，默认为False。如果列表中包含的是字符串，按字母串排序规则排序。可以使用key参数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34b35fc6-a26a-42c1-9990-575f8c10cd52",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "numbers=[12,34,3.14,99,-10]\n",
    "numbers.sort() # 默认升序排列\n",
    "numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90cafb4c-641f-44c0-a0df-5eeb7c443fa5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "numbers.sort(reverse=True) #降序排列\n",
    "numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16324eec-8f91-4800-a371-0a98bd61ae8b",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "numbers.sort(key=str)    #按转换为字符串后的大小升序排列\n",
    "numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "884ad53c-55a8-45a6-95bb-cc095952ae94",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b47b4dc6-39de-4b46-b892-47ed81f9acc5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ab', 'cde', 'fghl']"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str1= ['ab', 'cde', 'fghl']\n",
    "str1.sort() #字符串默认按照排序规则排列\n",
    "str1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "b7336796-4ed4-4086-ba56-d82777cdebb9",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ab', 'cde', 'fghl']"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str1.sort(key=len) #按字符串的长度升序排列\n",
    "str1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "cc99a877-6065-4cdf-ae2e-7a130fae9424",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['fghl', 'cde', 'ab']"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str1.sort(key=len,reverse=True) #利用reverse命令长度降序排列\n",
    "str1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "d396f0b9-1fe8-4abd-8bdf-8c90201b684a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<' not supported between instances of 'str' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mTypeError\u001B[0m                                 Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[52], line 2\u001B[0m\n\u001B[0;32m      1\u001B[0m nv\u001B[38;5;241m=\u001B[39m[\u001B[38;5;241m12\u001B[39m,\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mbus\u001B[39m\u001B[38;5;124m'\u001B[39m,\u001B[38;5;241m99\u001B[39m,\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mtrain\u001B[39m\u001B[38;5;124m'\u001B[39m] \u001B[38;5;66;03m#含有字符串和数字，不适用sort命令\u001B[39;00m\n\u001B[1;32m----> 2\u001B[0m \u001B[43mnv\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msort\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n",
      "\u001B[1;31mTypeError\u001B[0m: '<' not supported between instances of 'str' and 'int'"
     ]
    }
   ],
   "source": [
    "nv=[12,'bus',99,'train'] #含有字符串和数字，不适用sort命令\n",
    "nv.sort()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "894df65a-8583-4754-8808-8465e4a5ea2c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5764fff3-d425-43e5-b34d-397ab7c34138",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表函数</font>\n",
    "-常用列表函数有`len()`、`max()`、`min()`、`reversed()`、`sorted()`等   \n",
    "- `len()`函数，用于返回列表中所包含元素的个数    \n",
    "- `max()`函数，用于返回列表中元素的最大值。如果列表中包含的是字符串，也按字符串的比较大小方法排序返回最小值，列表中只能包含可相互比较的元素。    \n",
    "- `min()`函数，用于返回列表中所包含元素的最小值。同样`max()`规则相同。   \n",
    "- `reversed()`函数，将列表中的元素位置反向并返回可迭代的reversed对象。可以和`list()`函数联合起来使用得到列表\n",
    "- `sorted()`函数，对列表进行排序并返回新列表"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "964b9cce-5fec-405a-8cfd-753292aae846",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`reversed()`函数**   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d2e5f2f9-880c-4f86-8bda-0b4628c09f61",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<list_reverseiterator at 0x1dc915c00a0>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vehicle = ['train', 'bus', 'car', 'subway', 'ship', 'bicycle']\n",
    "reversed(vehicle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "9632a63a-d894-4448-83d7-8fb594db862d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bicycle', 'ship', 'subway', 'car', 'bus', 'train']"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(reversed(vehicle))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7ec47649-b5c5-4226-844d-e81243964d49",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<list_reverseiterator at 0x1dc927a9330>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nv=[12,'bus',99,'train']\n",
    "reversed(nv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "fffa1e61-ec5b-4feb-803a-0b67f3ecb5bd",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['train', 99, 'bus', 12]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " list(reversed(nv))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3870ec19-68dd-4667-a069-a1673db86ee7",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5171b3d4-f05b-4a35-b138-272b78d307a0",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "********\n",
    "**`sorted()`函数**   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "713ecebe-4b9b-402c-b89c-1aa9e03a4be4",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[12, 34, 3.14, 99, -10]\n",
      "[-10, 3.14, 12, 34, 99]\n"
     ]
    }
   ],
   "source": [
    "numbers=[12,34,3.14,99,-10]\n",
    "n1=sorted(numbers) #新列表\n",
    "print(numbers)\n",
    "print(n1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35be8c2d-6521-4888-9a33-559c0596fe47",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2151241-c095-47c6-8a3a-f6a63ac03261",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "> 思考：请比较sorted()函数和sort()方法的异同。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4820cac-441b-4676-bf6c-5a3d85ceb268",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表遍历</font>\n",
    "- 可以通过for语句或者while语句循环遍历列表中所有元素。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "417685a2-a2a7-4034-9835-b9aad92d910f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train bus car subway ship bicycle "
     ]
    }
   ],
   "source": [
    "vehicle=['train', 'bus', 'car', 'subway', 'ship', 'bicycle']\n",
    "for i in vehicle:\t\t#直接遍历每一个元素\n",
    "    print(i,end=' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "69d895f1-23b5-4d09-b300-613db4288d0f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train bus car subway ship bicycle "
     ]
    }
   ],
   "source": [
    " for i in range(len(vehicle)):\t#通过索引遍历每一个元素\n",
    "    print(vehicle[i],end=' ')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a089547b-f58e-4086-a5bb-965ca9fb7804",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "*****\n",
    "用while循环："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "7276f9eb-772a-4d4d-92c0-d435533cd62b",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train bus car subway ship bicycle "
     ]
    }
   ],
   "source": [
    "i=0\n",
    "while i<len(vehicle):\t#通过索引遍历每一个元素\n",
    "      print(vehicle[i],end=' ')\n",
    "      i+=1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52156c61-d080-4ba3-b916-625fa64eb2eb",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe6158c3-f15c-4866-bc84-bc190b53e561",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 列表的生成式</font>\n",
    "- 在Python中，列表还可以通过一种特殊的字面量语法来创建，这种语法叫做生成式。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "081a7670-f705-4e57-b0bc-e63a479ad6ca",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "*****\n",
    "### 方式一：通过`for`循环为空列表添加元素：    \n",
    "*创建一个由1到9的数字构成的列表：*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "98ddd846-0161-47be-9c75-1bb5f57698b2",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
     ]
    }
   ],
   "source": [
    "items1 = []\n",
    "for x in range(1, 10):\n",
    "    items1.append(x)\n",
    "print(items1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3082ad97-04e9-446c-a30d-19130ab998c8",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "*创建一个由个两个字符串中字符的笛卡尔积构成的列表：*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "0aac2018-f126-472e-9a69-3aec2bd17099",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['A1', 'A2', 'B1', 'B2', 'C1', 'C2']\n"
     ]
    }
   ],
   "source": [
    "items3 = []\n",
    "for x in 'ABC':\n",
    "    for y in '12':\n",
    "        items3.append(x + y)\n",
    "print(items3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6ffc69d-c4b2-4121-b73a-1bc870de3253",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "993c38a0-4535-4e5b-b625-8052a8a2fd1c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "*****\n",
    "### 方式二： 生成式创建列表：    \n",
    "*创建一个由1到9的数字构成的列表：*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51bbaf76-4626-4ca3-b6e4-7e27c49b1df5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items1 = [x for x in range(1, 10)]\n",
    "print(items1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58012d2d-0760-4929-b2f6-ef67a31671eb",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "items3 = [x + y for x in 'ABC' for y in '12']\n",
    "print(items3)  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "448ff8e2-8dc4-42eb-acf9-ce3bce5981cd",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "skip"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0708d373-9148-45eb-8c0c-ea8b9101cf1f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "> 生成式不仅代码简单优雅，而且性能也优于上面使用 `for` 循环和 `append` 方法向空列表中追加元素的方式。可以简单跟大家交待下为什么生成式拥有更好的性能，那是因为Python解释器的字节码指令中有专门针对生成式的指令（`LIST_APPEND`指令）；而 `for` 循环是通过方法调用（`LOAD_METHOD`和 `CALL_METHOD` 指令）的方式为列表添加元素，方法调用本身就是一个相对耗时的操作。对这一点不理解也没有关系，记住“**强烈建议用生成式语法来创建列表**”这个结论就可以了。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2017ce2-7b29-441e-89f4-092214eac909",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [],
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 列表\n",
    "-----\n",
    "### <font color = #DC143C> 嵌套的列表 </font>\n",
    "\n",
    "- 如果列表中的元素又是列表，那么我们可以称之为嵌套的列表。嵌套的列表可以用来表示表格或数学上的矩阵。\n",
    "\n",
    "- 例如：我们想保存5个学生3门课程的成绩，可以定义一个保存5个元素的列表保存5个学生的信息，而每个列表元素又是3个元素构成的列表，分别代表3门课程的成绩。但是，一定要注意下面的代码是有问题的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e019d9e7-aef4-4923-8844-dc5273d90ab5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": [],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "scores = [[0] * 3] * 5\n",
    "print(scores) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04f302b8-e786-4690-a87b-b68694535dbf",
   "metadata": {
    "editable": true,
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   "source": [
    "看上去我们好像创建了一个`5 * 3`的嵌套列表，但实际上当我们录入第一个学生的第一门成绩后，你就会发现问题来了，我们看看下面代码的输出。"
   ]
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    "scores[0][0] = 95\n",
    "print(scores)"
   ]
  },
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   "source": [
    "..."
   ]
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  {
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   "metadata": {
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   "source": [
    "> 我们不去过多的解释为什么会出现这样的问题，如果想深入研究这个问题，可以通过[Python Tutor](<http://www.pythontutor.com/visualize.html>)网站的可视化代码执行功能，看看创建列表时计算机内存中发生了怎样的变化，下面的图就是在这个网站上生成的。建议大家不去纠结这个问题，现阶段只需要记住不能用`[[0] * 3] * 5]`这种方式来创建嵌套列表就行了。"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "**正确的创建嵌套列表方式：**"
   ]
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  {
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   "id": "cdb8678b-451e-4bd8-a497-1a0c2aa1dbe9",
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   },
   "outputs": [],
   "source": [
    "scores = [[0] * 3 for _ in range(5)]\n",
    "scores[0][0] = 95\n",
    "print(scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab1bc298-4038-4a1b-a2cc-c357b4f67d9b",
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   "source": [
    "..."
   ]
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  {
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   "source": [
    "### 简单的总结\n",
    "\n",
    "Python中的列表底层是一个可以动态扩容的数组，列表元素在内存中也是连续存储的，所以可以实现随机访问（通过一个有效的索引获取到对应的元素且操作时间与列表元素个数无关）。我们暂时不去触碰这些底层存储细节以及列表每个方法的渐近时间复杂度（执行这个方法耗费的时间跟列表元素个数的关系），等需要的时候再告诉大家。现阶段，大家只需要知道**列表是容器**，可以**保存各种类型的数据**，**可以通过索引操作列表元素**，知道这些就足够了。"
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   "source": [
    "## 作业：\n",
    "- 1、给定一个由10个整数值构成的列表[10,9,8,7,6,5,4,3,2,1]，编程只对列表中下标为奇数的元素进行升序排列。    \n",
    "- 2、用户分别从键盘输入4个整数和3个整数组成两个列表list1和list2，将列表list2合并到list1中，并在list1末尾再添加两个数字90和100，然后对list1降序排列，最后输出最终的列表list1。    \n",
    "- 3、某公司股票近一段时间的收盘价（单位：元）分别为：12.04, 11.15, 13.47 , 13.58, 12.04, 12.04, 11.15, 12.58, 11.15，请建立一个列表(data)存储这些数据。请编写程序解决如下问题：    \n",
    "    + 上述一共有几个数据？\n",
    "    + 统计收盘价为12.04元的次数；\n",
    "    + 找出收盘价中的最小数据，并删除首次出现的最小数据，最后显示列表data。"
   ]
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